Systems and methods for respiratory health management

ABSTRACT

Systems and methods for respiratory health management are provided. An air filtration and analysis system may comprise an apparatus configured to be worn by a user. The apparatus may comprise a filtration device. The system may also include a plurality of sensors configured to collect data. A portion of the sensor data may be indicative of (i) one or more characteristics of the air inhaled and/or exhaled by the user, and/or (ii) an environment in which the user is located. At least one sensor and/or the apparatus may be in communication with a processor that is configured to analyze the collected sensor data.

CROSS-REFERENCE

This application is a continuation application of U.S. patentapplication Ser. No. 16/041,401, filed on Jul. 20, 2018, which is acontinuation of International Application No. PCT/US2017/015816, filedon Jan. 31, 2017, which claims the benefit of U.S. Provisional PatentApplication No. 62/289,445, filed Feb. 1, 2016, U.S. Provisional PatentApplication No. 62/289,457, filed Feb. 1, 2016, U.S. Provisional PatentApplication No. 62/289,480, filed Feb. 1, 2016, and U.S. ProvisionalPatent Application No. 62/289,546, filed Feb. 1, 2016, whichapplications are incorporated herein by reference in their entiretiesfor all purposes.

BACKGROUND

According to the United States Environmental Protection Agency (EPA),air pollutants can cause numerous negative health impacts, such as noseand throat discomfort, headache, allergic airway and skin reactions,dizziness, trouble breathing, coughing, pain, and reduced lung function.According to the World Health Organization (WHO), air pollutants ofmajor health concern include bacteria and viruses (e.g. influenza strainH1N1), cigarette smoke, radon, particulate matter, carbon monoxide,ozone, nitrogen dioxide and sulfur dioxide. Outdoor and indoor airpollution often cause respiratory and other diseases, which can befatal. In 2012, according to the World Health Organization, one in eightof total global deaths were the result of air pollution exposure. Thisfinding more than doubles previous estimates and confirms that airpollution is now the world's largest single environmental health risk.The major causes of death due to air pollution are ischemic heartdisease (40%), stroke (40%), chronic obstructive pulmonary disease(COPD) (11%), lung cancer (6%), and acute lower respiratory infectionsin children (3%). The air we inhale and exhale also contains chemicalsthat may not be harmful, but may be perceived to be unpleasant, such aspet odors or food smells. Health and performance relevant parametersinclude breathing rate, breathing volume, gas temperature and humidity,and the levels of gasses and chemicals, such as oxygen and carbondioxide, in the exhaled air.

Air filtration devices can be used to mitigate the adverse healtheffects of airborne particulate matter, pathogens, allergens, and otherpollutants. Some of these devices may be provided, for example, as masksthat are worn over a person's mouth and/or nose. Most of these devicesare passive filters that are designed to filter out a generic set ofpollutants. These devices generally are not customized for each user'sneeds. Given their passive nature, these devices are also not configuredto sense and adapt to changes in environmental conditions and/or auser's health conditions. In terms of aesthetics and ease of use, thebulk of these devices are typically unattractive and hinder the user'sability to communicate, as they are usually worn over a large part ofthe face.

In light of the above, there is a need for systems and methods that canaccurately sense the surrounding environment and monitor users' healthand health conditions, and that provide improved filtering performancefor individual users. There is also a need for airfiltration/respiratory devices that are effective, comfortable, easy touse by people suffering from various impairments, compact, aestheticallypleasing, can notify users of air pollution hazards and/or recommendcertain corrective actions to users to improve their health and/orwell-being, and that do not hinder a user's ability to communicate withothers.

SUMMARY

The systems and methods described herein relate to the filtration and/orsensing of the air inhaled and/or exhaled by a user. The air that weinhale may contain numerous substances that are unpleasant or harmful.The systems and methods described herein may allow partial or completefiltration of these substances during inhalation, mitigating the harmfuleffects that these substances cause to a user's health. The systems andmethods may allow users to obtain a customized filtration performance(such as a high level of filtration toward one or more harmfulsubstances, a low level of filtration, or even a complete lack offiltration) based on the user's health concerns (such as allergies orresidence in highly-polluted areas) or personal preferences (such asathletic performance). The systems and methods may comprise replaceablefilter modules that allow for the easy replacement of filters, such aswhen a filter suffers from reduced performance due to extensive use orwhen a user's filtration needs or desires change.

Meanwhile, the air that we exhale can give significant insight into aperson's current and future performance and health. The systems andmethods described herein may allow the air exhaled by a user to besensed and analyzed to provide information relevant to the health of auser. The sensing data may be utilized for the purposes healthmaintenance, prevention, and/or prediction. The sensing data maycomprise information about the amount of a harmful substance to which auser is exposed. In some cases, the systems and methods described hereinmay both sense the air exhaled by a user and filter the air inhaled bythe user. In other cases, the systems and methods may only sense the airexhaled by the user. In such cases, the sensing data may comprisedinformation about the health status of a user. For instance, the sensingdata may comprise information about vital signs of a user, such as theuser's breathing rate. In some cases, the sensing data may serve tomonitor the user for signs of sleep apnea or other sleeping disorders.In some cases, the sensing data may be used to predict the onset ofasthma attacks. The sensing data may also be used to track the real-timeperformance of the filter, if the user's device includes such a filter.

The systems and methods described herein may notify users of actionsthat they can take to protect their health based on the sensing dataand/or the filtration performance. For instance, the systems and methodsmay notify users that they are in areas of dangerously polluted air andtell them to go inside if they do not have adequate filtration. In somecases, the systems and methods may notify a user that they may soon havean asthma attack and provide suggestions for alleviating the symptoms,such as that the user should pre-emptively use their asthma inhaler. Insome cases, the systems and methods may notify a user that they aredisplaying symptoms of sleep apnea and provide suggestions for reducingthe severity of these symptoms.

In one aspect, an air filtration and analysis system comprises anapparatus configured to be worn by a user and a plurality of sensorsconfigured to collect data. The apparatus may comprise a filtrationdevice. A portion of the sensor data may be indicative of (i) one ormore characteristics of the air inhaled and/or exhaled by the user,and/or (ii) an environment in which the user is located. At least onesensor and/or the apparatus may be in communication with a processorthat is configured to analyze the collected sensor data. The filtrationdevice may be configured to reduce one or more elements from the airinhaled by the user. The filtration device may be configured to beplaced within the nasal passages of the user. The plurality of sensorsmay comprise chemical sensors, pressure and air flow sensors, heart-ratemonitors, GPS sensors, temperature sensors, or inertial sensors. Theplurality of sensors may comprise a first set of sensors that is locatedwith or on the filtration device, and a second set of sensors that islocated remote to the filtration device. The plurality of sensors may beconfigured to collect the sensor data at different predeterminedsampling frequencies.

The processor may be configured to effect operation of the filtrationsystem and/or at least one sensor based on the analyzed sensor data, soas to reduce an impact of one or more elements on the user's health. Theprocessor may be configured to perform one or more of the followingsteps: (1) calibrate at least one sensor against a baseline sensorreference; (2) check whether at least one sensor is operating normallyor whether the sensor is defective; or (3) correct for sensor drift,error or bias. The processor may be configured to analyze the sensordata by cross-checking an accuracy of each set of sensor data againstother different types of sensor data. The processor may be configured toanalyze the sensor data by correlating sensor data from differentsources. The processor may configured to assign weights to the sensordata based on an accuracy and/or inherent sensing characteristics ofeach of the plurality of sensors. The processor may be configured toanalyze the sensor data using statistical methods. The processor may beconfigured to analyze the sensor data by combining different sets ofsensor data in a manner that compensates for the deficiencies ofindividual sensors or type of sensors.

The processor may be located on a mobile device or a wearable devicethat is carried or worn by the user, and/or on a server that is remoteto the user. The processor may be configured to compress the collectedsensor data and store the compressed data in a memory. The processor maybe configured to effect the operation of the filtration device and/orthe at least one sensor, by programming and customizing the filtrationdevice and/or the at least one sensor (1) to meet the user'sphysiological needs and activities, and/or (2) based on the user's localenvironment. The processor may be configured to analyze the collectedsensor data so to determine (1) a health status and/or medicalconditions of the user, and/or (2) a type of activity that the user isperforming. The processor may be configured to analyze the collectedsensor data so as to determine the user's proximity to known sources ofpollution, environment, time of day, and/or season. The processor may beconfigured to effect the operation of the filtration device and/or theat least one sensor, such that the filtration device and/or the at leastone sensor is configured to dynamically and automatically adapt inreal-time as the user moves from one location to another location, astime of day changes, as season changes, and/or depending on changes inthe user's health status. The processor may be configured to effect theoperation of the filtration device and/or the at least one sensor, by(1) selectively activating or de-activating the at least one sensor,and/or (2) adjusting a sensitivity level, sensing range, or samplingfrequency of the at least one sensor.

In another aspect, a method for filtering and analyzing inhaled and/orexhaled air comprises obtaining data collected using a plurality ofsensors, analyzing the collected sensor data, and effecting operation ofthe filtration device and/or at least one sensor of said plurality basedon the analyzed sensor data. A portion of the sensor data may beindicative of (i) one or more characteristics of the air inhaled and/orexhaled by a user, and/or (ii) an environment in which the user islocated. The filtration device may be configured to be worn by the user.

In another aspect, a system for filtering and analyzing inhaled and/orexhaled air comprises a server and a processor configured to execute aset of software instructions. The server may comprise a memory forstoring data collected using a plurality of sensors operably coupled toa filtration device. A portion of the sensor data may be indicative of(i) one or more characteristics of the air inhaled and/or exhaled by auser, and/or (ii) an environment in which the user is located. Thefiltration device may be configured to be worn by the user. Theprocessor may analyze the collected sensor data and effect operation ofthe filtration device and/or at least one sensor based on the analyzedsensor data.

In another aspect, a tangible computer readable medium storesinstructions that, when executed by a processor, causes the processor toperform a computer-implemented method for filtering and analyzinginhaled and/or exhaled air. The method may comprise obtaining datacollected using a plurality of sensors, analyzing the collected sensordata, and effecting operation of a filtration device and/or at least onesensor of said plurality based on the analyzed sensor data. A portion ofthe sensor data may be indicative of (i) one or more characteristics ofthe air inhaled and/or exhaled by a user, and/or (ii) an environment inwhich the user is located. The filtration device may be configured to beworn by the user.

In another aspect, a system for analyzing and displaying sensor data forpollution and user health monitoring comprises a processor incommunication with a plurality of sensors. The processor may beconfigured to receive the sensor data collected by the plurality ofsensors, analyze the collected sensor data to thereby generate aplurality of pollution and health metrics including a healthrecommendation that are specific to the user, and provide the pluralityof pollution and health metrics on at least one user device. Theplurality of sensors may comprise: (1) a first set of sensors located inproximity to a respiratory passageway of a user, and configured tocollect sensor data associated with one or more elements in air inhaledby the user, and (2) a second set of sensors located remotely from theuser and configured to collect a plurality of different sensor data. Theplurality of pollution and health metrics may be configured to bedisplayed as a set of graphical visual objects on a graphical display ofthe user device.

The plurality of pollution and health metrics may include a detectedlevel of the one or more elements in the air within the vicinity of theuser. The plurality of pollution and health metrics may include aprediction of whether a level of the one or more elements is expected toincrease or decrease within the vicinity of the user, and/or a rate ofthe increase or decrease. The health recommendation may include awarning of an impact to the user's health should the user continue toinhale the air containing the one or more elements. The healthrecommendation may include a numerical value that is indicative of apredicted impact of the one or more elements on the user's health. Thehealth recommendation may include a suggested corrective action tominimize inhalation of the air containing the one or more elements. Thesuggested corrective action may include a recommendation that the usertakes a different route or relocate to a different area. The suggestedcorrective action may include a recommendation that the user reduces orcease performing any strenuous physical activity. The suggestedcorrective action may include a recommendation that the user use an airfiltration device that is configured to remove or reduce the one or moreelements from the inhaled air.

The processor may be configured to generate an audio, visual and/ortactile signal to notify the user when the numerical value exceeds apredetermined threshold. The processor may be configured to generate anaudio, visual and/or tactile signal to notify the user when a level ofthe one or more elements in the inhaled air exceeds a predeterminedlevel. The processor may be configured to analyze the collected sensordata by correlating the user's medical or health condition to a level ofthe one or more elements in the inhaled air. The processor may beconfigured to analyze the collected sensor data so as determine which ofthe one or more elements have a greater impact or lesser impact to theuser's health. The processor may be configured to adjust the healthrecommendation accordingly based on detected changes to the user'shealth. The processor may be configured to update the plurality ofpollution and health metrics in real-time based on the collected sensordata.

In another aspect, a method of analyzing and displaying sensor data forpollution and user health monitoring comprises receiving the sensor datacollected by a plurality of sensors and analyzing the collected sensordata to thereby generate a plurality of pollution and health metricsincluding a health recommendation that are specific to the user. Theplurality of sensors may comprise: (1) a first set of sensors located inproximity to a respiratory passageway of a user, and configured tocollect sensor data associated with one or more elements in air inhaledby the user, and (2) a second set of sensors located remotely from theuser and configured to collect a plurality of different sensor data. Theplurality of pollution and health metrics may be configured to bedisplayed as a set of graphical visual objects on a graphical display ofat least one user device.

In another aspect, a tangible computer readable medium storesinstructions that, when executed by a processor, causes the processor toperform a computer-implemented method for analyzing and displayingsensor data for pollution and user health monitoring. The method maycomprise receiving the sensor data collected by a plurality of sensors,analyzing the collected sensor data to thereby generate a plurality ofpollution and health metrics including a health recommendation that arespecific to the user, storing the plurality of pollution and healthmetrics in a memory, and providing the plurality of pollution and healthmetrics on at least one user device. The plurality of sensors maycomprise: (1) a first set of sensors located in proximity to arespiratory passageway of a user, and configured to collect sensor dataassociated with one or more elements in air inhaled by the user, and (2)a second set of sensors located remotely from the user and configured tocollect a plurality of different sensor data. The plurality of pollutionand health metrics may be configured to be displayed as a set ofgraphical visual objects on a graphical display of the user device.

In another aspect, an air filtration and sensing apparatus comprises afiltration device configured to be worn by a user, and configured toreduce one or more elements from air inhaled by the user, and aplurality of sensors operably coupled to the filtration device. Theplurality of sensors may be configured to detect concentration levels ofthe one or more elements in the inhaled and/or exhaled air. At least ofone sensor of said plurality may be powered by energy extracted from theuser's motion and/or respiration.

The energy may be extracted using power generators comprisingpiezoelectric elements, inductive elements, and/or windmills. Theapparatus may comprise an energy storage device configured to storeand/or discharge the energy. The plurality of sensors may be configuredto operate in a plurality of operational modes including a power savingmode and a performance mode. The performance mode may consume more powercompared to the power saving mode. The apparatus may comprise one ormore cooling mechanisms configured to improve heat dissipation from theplurality of sensors during operation of said sensors.

In another aspect, a method for powering at least one sensor in an airfiltration and sensing apparatus comprises extracting, using one or moreenergy collection elements, energy from a user's motion and/orrespiration and powering the at least one sensor selected from aplurality of a sensors using the extracted energy. The plurality ofsensors may be configured to detect concentration levels of one or moreelements in air inhaled and/or exhaled by the user. The plurality ofsensors may be operably coupled to a filtration device. The filtrationdevice may be configured to be worn by the user.

In another aspect, an air filtration apparatus comprises a filter holderconfigured to receive and interchange therein a plurality of differentcartridge filters. The plurality of different cartridge filters may beconfigured to meet filtering requirements and health needs of differentusers for a plurality of different environments. The plurality ofdifferent cartridge filters may be configured to reduce one or moreelements in the air inhaled by a user.

The filter holder may comprise a partial or full nasal insert. Thefilter holder may be part of a facial mask or respirator. The pluralityof different cartridge filters may be configured to be interchangedand/or mounted onto the filter holder using a quick release mechanism.The plurality of different cartridge filters may be configured to beinterchanged and/or mounted onto the filter holder without the use oftools. At least one of the cartridge filters may comprise a mesh. Themesh may comprise a nanofiber mat. The mesh may comprise activatedcarbon. The mesh may comprise a plurality of pores having the same ordifferent shapes and/or sizes. The mesh may comprise a nanostructuremesh configured to allow for increased airflow. The mesh may be arrangedin a manner such that filtration of air occurs in a predetermineddirection during inhalation. The apparatus may comprise one or moredilation structures for increasing airflow. At least one of the filtercartridges may comprise a filtering element that is capable of adjustingits position and/or shape to increase airflow.

In another aspect, a method for assembling an air filtration apparatuscomprises attaching a first cartridge filter into a filter holder of theair filtration apparatus, removing the first cartridge filter from thefilter holder, and attaching a second cartridge filter into the filterholder. The filter holder may be configured to receive and interchangetherein a plurality of different cartridge filters. The plurality ofdifferent cartridge filters may be configured to reduce one or moreelements from air inhaled by a user. The first cartridge filter may becustomized to meet a first set of filtering requirements and healthneeds of the user. The second cartridge filter may be customized to meeta second set of filtering requirements and health needs that aredifferent from the first set of filtering requirements and health needsof the user.

In another aspect, a method of displaying sensor data for pollution anduser health monitoring comprises receiving an input from a user on auser device and displaying, in response to the received input, theplurality of pollution and health metrics as a set of graphical visualobjects on a graphical display. The input may comprise a request fromthe user associated with a plurality of pollution and health metricsincluding a health recommendation that are specific to the user. Atleast one of the graphical visual objects may be configured to change inreal-time to reflect changes in the plurality of pollution and healthmetrics as the metrics are being monitored by a plurality of sensors.The user device may comprise a mobile device. The graphical display maybe provided on the user device.

In another aspect, a nasal apparatus comprises a housing comprising acavity located therein for permitting airflow into and out of a user'sbody and a retention mechanism configured to releasably couple thehousing to a portion of the user's nasal passageway, so as to affix thenasal apparatus on the user's nose without requiring the use of one ormore external fixation devices. The retention mechanism may be locatedon a peripheral portion of the housing. The retention mechanism maycomprise at least one protrusion extending from the peripheral portionof the housing. The retention mechanism may comprise a first protrusionand a second protrusion that are located on opposite ends of theperipheral portion of the housing. The at least one protrusion may beconfigured to be releasably coupled to the portion of the user's nasalpassageway. The at least one protrusion may be shaped to releasablycouple to natural cartilage and/or tissue pockets located in the portionof the user's nasal passageway. The retention mechanism may beconfigured to releasably couple the housing to the portion of the user'snasal passageway via a predefined motion. The predefined motion patternmay comprise at least one rotary motion of the nasal apparatus. Theapparatus may have a shape and/or profile that minimizes physicalinterference with lip movement of the user when the apparatus is beingworn on the user's nose. The apparatus may not encroach on the user'supper lip when the apparatus is being worn on the user's nose. Theapparatus may not visually obstruct lip movement of the user when theapparatus is being worn on the user's nose.

These and other embodiments are described in further detail in thefollowing description related to the appended drawing figures.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth with particularity inthe appended claims. A better understanding of the features andadvantages of the present invention will be obtained by reference to thefollowing detailed description that sets forth illustrative embodiments,in which the principles of the invention are utilized, and theaccompanying drawings of which:

FIG. 1A shows a schematic of a system comprising one or more airfiltration and sensing devices interacting within a network.

FIG. 1B shows a schematic of a system comprising one or more air sensingdevices interacting within a network.

FIG. 2A illustrates exemplary components in an air filtration andsensing device.

FIG. 2B illustrates exemplary components in an air sensing device.

FIG. 3 shows a schematic of a user utilizing an air filtration andsensing device.

FIG. 4A shows an air filtration and sensing device worn inside of auser's nasal passage.

FIG. 4B shows an air filtration and sensing device worn over a user'snose and mouth.

FIG. 5A shows a front view of an intranasal air filtration and sensingdevice worn entirely within a user's nasal passage.

FIG. 5B shows a side view of an intranasal air filtration and sensingdevice worn entirely within a user's nasal passage.

FIG. 5C shows a front view of an intranasal air filtration and sensingdevice worn partially within a user's nasal passage.

FIG. 5D shows a side view of an intranasal air filtration and sensingdevice worn partially within a user's nasal passage.

FIGS. 6A and 6B show a schematic of a cartridge-based intranasal airfiltration and sensing device.

FIGS. 7A and 7B show a schematic of a cartridge-based intranasal airfiltration device comprising a plurality of filtration layers.

FIG. 8 shows a flowchart of a method of providing a user with acustomized air filtration device.

FIG. 9A shows a schematic of a cartridge-based intranasal air filtrationdevice comprising a plurality of filtration elements, during a period inwhich a user is inhaling.

FIG. 9B shows a schematic of a cartridge-based intranasal air filtrationdevice comprising a plurality of filtration elements, during a period inwhich a user is exhaling.

FIG. 10A shows a schematic of a cartridge-based intranasal airfiltration and sensing device comprising a dilation structure to openthe nasal passage for increased airflow.

FIG. 10B shows a schematic of a dilation structure to open the nasalpassage for increased airflow.

FIG. 11A shows a cartridge-based air filtration device in a positionallowing increased filtration and reduced airflow during a period inwhich a user is inhaling.

FIG. 11B shows a cartridge-based air filtration device in a positionallowing reduced filtration and increased airflow during a period inwhich a user is exhaling.

FIG. 12 shows a schematic for an air sensing device utilizing an opticaldetection scheme.

FIG. 13A shows a schematic for an air sensing device utilizing anoptical detection scheme with a reduced optical path length comprisingone or more mirrors.

FIG. 13B shows a schematic for an air sensing device utilizing anoptical detection scheme with a reduced optical path length comprisingone or more polarizing elements.

FIG. 14A shows a schematic for an air sensing device comprising aplurality of sensing elements arranged in a linear manner.

FIG. 14B shows a schematic for an air sensing device comprising aplurality of sensing elements arranged in a staggered manner.

FIG. 15A shows a schematic for a device capable of converting energyfrom breathing to electrical energy comprising a piezoelectric elementattached to flexible vanes of a one-way valve, during a period in whicha user is inhaling.

FIG. 15B shows a schematic for a device capable of converting energyfrom breathing to electrical energy comprising a piezoelectric elementattached to flexible vanes of a one-way valve, during a period in whicha user is exhaling.

FIG. 15C shows a schematic for a device capable of converting energyfrom breathing to electrical energy comprising a piezoelectric elementattached to the surface of an air-carrying tube, during a period inwhich a user is inhaling.

FIG. 15D shows a schematic for a device capable of converting energyfrom breathing to electrical energy comprising a piezoelectric elementattached to the surface of an air-carrying tube, during a period inwhich a user is exhaling.

FIG. 16 shows a flowchart for a method of utilizing data from aplurality of sensors to construct a personalized pollution exposurescore to a user wearing an air filtration and sensing device.

FIG. 17 shows a graphical user interface for use with an air filtrationand sensing device that displays a user's pollution exposure while usingthe device and the user's expected exposure without the device.

FIG. 18 shows a graphical user interface for use with an air filtrationand sensing device that displays pollution exposure levels in differentlocations near a user.

FIG. 19 shows a graphical user interface for use with an air filtrationand sensing device that displays a user's pollution exposure score.

FIG. 20A shows a perspective view of a nosebud that can be used in anair filtration and sensing device.

FIG. 20B shows a cross-sectional view of the air nosebud of FIG. 20A.

FIG. 21A shows a top view of a nosebud that can be used in an airfiltration and sensing device.

FIG. 21B shows a first cross-sectional view of the nosebud of FIG. 21A.

FIG. 21C shows a second cross-sectional view of the nosebud of FIG. 21A.

FIG. 21D shows exemplary dimensions of the nosebud of FIG. 21A.

FIG. 22A shows a magnetic resonance image (MRI) of pockets within thenose that may accept an air filtration and sensing device utilizing anosebud.

FIG. 22B shows an air filtration and sensing device utilizing a nosebudthat is anchored in the pockets of the nose.

FIG. 22C shows a first step of inserting an air filtration and sensingdevice utilizing a nosebud into the nose.

FIG. 22D shows a second step of inserting an air filtration and sensingdevice utilizing a nosebud into the nose.

FIG. 22E shows a third step of inserting an air filtration and sensingdevice utilizing a nosebud into the nose.

DETAILED DESCRIPTION

While various embodiments of the invention have been shown and describedherein, it will be obvious to those skilled in the art that suchembodiments are provided by way of example only. Numerous variations,changes, and substitutions may occur to those skilled in the art withoutdeparting from the invention. It should be understood that variousalternatives to the embodiments of the invention described herein may beemployed.

As used herein, the term “pollution” or “pollutant” refers to a range ofgases, chemicals, odors, particulate matter, and biological materialsthat may be detrimental and/or undesirable to human health uponinhalation, or that may be perceived to be unpleasant. Examples ofpollutants include, but are not limited to radon, cigarette smoke,carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbon compounds,fluorocarbon compounds, hydrofluorocarbon compounds, chlorofluorocarboncompounds, ozone (O₃) nitrous oxides (NO_(x)), sulfur-containingcompounds, volatile organic compounds (VOCs) combustion-generatedparticulate matter such as soot, fine particulate matter with a diameterless than 2.5 μm (PM2.5), coarse particulate matter with a diameterbetween 2.5 μm and 10 μm (PM10), dander, plant pollens, bacteria,viruses, and pet odors. The term “pollution” or “pollutant” may refer toany material that may be detrimental to human health upon inhalation, orthat may be perceived to be unpleasant, as is known to one having skillin the art.

As used herein, the term “air quality” refers to metrics based on one ormore constituents of air that are associated with or staticallycorrelated with human health effects and/or with a human's perception ofthe air. Metrics of air quality can be based on direct measurements ofdust and particulate matter. Metrics of air quality can be based onmeasurements of proxies for particulate matter (e.g. gasses that areclosely associated with particulate matter, such as carbon monoxidecreated during combustion). Metrics of air quality can be based onmeasurements of other constituents of air composition, such as plantpollen and/or moisture content. Metrics of air quality can include anair quality index (AQI) used by a government to indicate a relative airquality hazard level. For instance, the air quality index may be theUnited States Environmental Protection Agency's Air Quality Index,Canada's Air Quality Health Index, the Chinese Ministry of EnvironmentalProtection's Air Pollution Index, the Indian Ministry for Environment,Forests and Climate Change's National Air Quality Index, Mexico City'sMetropolitan Air Quality Index, Europe's Common Air Quality Index, orany other AQI as is known to one having skill in the art.

As used herein, the term “natural air flow” refers to air that is movingover or through the human body during the inhalation and exhalationcycle.

As used herein, the term “sensor” refers to a device that uses one ormore electronic, chemical, mechanical, or optical means to convert theconcentration of a compound (e.g. the amount of dust in the air) into asignal (typically, an electrical signal) that can be communicated to amicroprocessor for further use, storage, and transmission.

As used herein, the term “sensor system” refers to a combination ofcircuit elements that together form a system capable of measuring,processing, storing, and/or transmitting one or more parameters. Asensor system may consist of one or more components taken from thefollowing list: a power source, a power regulator, a microcontroller, amemory element, a signal conditioning element, a data logging element, adata transmission element, and one or more sensors.

The systems and methods disclosed herein relate to air filtration andsensing. The systems and methods may allow filtration and sensing of aircomposition and pollutants with compact devices that are capable ofbeing worn in, on, or near the point at which air is inhaled (e.g. overthe mouth or within the nasal passages). The devices may require aminimal supply of electrical power. The devices may also communicate theresults of air composition measurements to a network, allowing advancedanalysis of air composition results that are collected and/or aggregatedfrom a large number of users. For instance, the analysis may comprise“big data” techniques. The analysis may produce information that isindicative of the pollution in an area, the type of pollutants thatusers are inhaling, the respiratory systems exhibited by users in aregion, the demographics (such as age, sex, or profession) of users in aregion, and/or the types of activity engaged in by users in a region.This information can be utilized to provide recommendations forcorrective actions to be taken by a user in order to improve the user'shealth and wellbeing.

FIG. 1A shows a schematic of a system comprising one or more airfiltration and sensing devices interacting with a data network. The airfiltration and sensing system 100 may comprise a wearable air filtrationand sensing device 110, a user device 120, a server 130 comprising asensing analysis module 132, a network 140, and a database 150.

Each of the components 110, 120, 130, 132, and 150 may be operativelyconnected to one another via network 140 or any type of communicationlinks that allows transmission of data from one component to another.The sensing analysis module may be configured to analyze input data fromthe user device and/or wearable device to detect and/or monitor aircomposition and pollution, and to provide information (e.g.,recommendations) to assist a user in mitigating the effects of airpollution on the user's health. The sensing analysis module may beimplemented anywhere within the system, and/or outside of the system. Insome embodiments, the sensing analysis module may be implemented on theserver. In other embodiments, the sensing analysis module may beimplemented on the user device. Additionally, the sensing analysismodule may be implemented on the wearable device. In some furtherembodiments, a plurality of sensing analysis modules may be implementedon one or more servers, user devices, and/or wearable devices.Alternatively, the sensing analysis module may be implemented in one ormore databases. The sensing analysis module may be implemented usingsoftware, hardware, or a combination of software and hardware in one ormore of the above-mentioned components within the system.

The wearable air filtration and sensing device 110 is configured to beworn by a user. For example, the device can be worn in, on, or near thepoint at which air is inhaled (e.g., within the nasal passage or overthe mouth). The device 110 can be configured to obtain sensors readingsof air pollution and composition and to filter the inhaled air. Thewearable device may comprise a filtration module 112. The filtrationmodule can filter the air to reduce the amount of pollutants passingfrom the atmosphere into the user's lungs, as described herein. Thewearable device may also comprise a sensing module 114. The sensingmodule can detect and/or measure the presence and/or level of one ormore chemicals or pollutants in a user's vicinity, as described herein.The wearable device may further comprise a transmitter 116. Thetransmitter can transmit various information to one or more user devices120. Such information may include the type and/or level of pollutants inthe user's vicinity, the user's health conditions, respiratory behavior,performance of the filtration module, reduction of pollutants from theinhaled air, etc. In some embodiments, the transmitter can transmit theinformation directly to the sensing analysis module on server 130 foranalysis of the air pollution and/or the user's state of health.

The transmitter may be a wired transmitter. The transmitter may be awireless transmitter. The transmitter may communicate informationobtained by the sensing module via a wireless communication channel toone or more user devices 120. The user device may be a smartphone or anyother portable electronic device. The wireless communication may be viaBluetooth communication. The wireless communication may be via Wi-Ficommunication. The wireless communication may be via any other wirelesscommunication known to one skilled in the art. In some cases, the airfiltration and sensing device 110 may also include a receiver that isconfigured to receive information from the user device and/or othercomponents in system 100 (e.g., sensing analysis module, server,database, etc.). In some embodiments, the transmitter may be replaced bya transceiver that is capable of providing two-way communication betweenthe wearable device and other components within system 100.

The transmitter may transmit raw sensor data or processed sensor data.Some or all processing of the sensor data may be performed on thewearable device, user device, and/or sensing analysis module. Forinstance, any of the aforementioned components may comprise hardware orsoftware elements that allow the sensor data obtained by the sensingmodule to be converted into electronic representations, and that canprocess the electronic representations to extract, for instance,measured values of the concentrations of the air pollutants. User device120 may be a computing device configured to perform one or moreoperations consistent with the disclosed embodiments.

Examples of user devices may include, but are not limited to, mobiledevices, smartphones/cellphones, tablets, personal digital assistants(PDAs), laptop or notebook computers, desktop computers, media contentplayers, television sets, video gaming station/system, virtual realitysystems, augmented reality systems, microphones, or any electronicdevice capable of analyzing, receiving, providing or displaying certaintypes of data (e.g., air pollution data, health impact, healthrecommendation, user's health status, etc.) to a user. The user devicemay be a handheld object. The user device may be portable. The userdevice may be carried by a human user. In some cases, the user devicemay be located remotely from a human user, and the user can control theuser device using wireless and/or wired communications.

User device 120 may include one or more processors that are capable ofexecuting non-transitory computer readable media that may provideinstructions for one or more operations consistent with the disclosedembodiments. The user device may include one or more memory storagedevices comprising non-transitory computer readable media includingcode, logic, or instructions for performing the one or more operations.The user device may include software applications that allow the userdevice to communicate with and transfer data between wearable device110, server 130, sensing analysis module 132, and/or database 150. Theuser device may include a communication unit, which may permit thecommunications with one or more other components in system 100. In someinstances, the communication unit may include a single communicationmodule, or multiple communication modules. In some instances, the userdevice may be capable of interacting with one or more components insystem 100 using a single communication link or multiple different typesof communication links.

User device 120 may include a display. The display may be a screen. Thedisplay may or may not be a touchscreen. The display may be alight-emitting diode (LED) screen, OLED screen, liquid crystal display(LCD) screen, plasma screen, or any other type of screen. The displaymay be configured to show a user interface (UI) or a graphical userinterface (GUI) rendered through an application (e.g., via anapplication programming interface (API) executed on the user device).The GUI may show images that permit a user to view various informationrelating to air pollution in the user's vicinity, performance of thefiltration module, etc. The user device may also be configured todisplay webpages and/or websites on the Internet. One or more of thewebpages/websites may be hosted by server 130 and/or rendered by sensinganalysis module 132.

A user may navigate within the GUI through the application. For example,the user may select a link by directly touching the screen (e.g.,touchscreen). The user may touch any portion of the screen by touching apoint on the screen. Alternatively, the user may select a portion of animage with aid of a user interactive device (e.g., mouse, joystick,keyboard, trackball, touchpad, button, verbal commands,gesture-recognition, attitude sensor, thermal sensor, touch-capacitivesensors, or any other device). A touchscreen may be configured to detectlocation of the user's touch, length of touch, pressure of touch, and/ortouch motion, whereby each of the aforementioned manners of touch may beindicative of a specific input command from the user.

User device 120 may include smartwatches, wristbands, glasses, gloves,headgear (such as hats, helmets, virtual reality headsets, augmentedreality headsets, headmounted devices (HMD), headbands), pendants,armbands, leg bands, shoes, vests, motion sensing devices, etc. Thewearable device may be configured to be worn on a part of a user's body(e.g., a smartwatch or wristband may be worn on the user's wrist). Theuser device may include one or more types of sensors. Examples of typesof sensors may include inertial sensors (e.g., accelerometers,gyroscopes, and/or gravity detection sensors, which may form inertialmeasurement units (IMUs)), location sensors (e.g., global positioningsystem (GPS) sensors, mobile device transmitters enabling locationtriangulation), heart rate monitors, external temperature sensors, skintemperature sensors, capacitive touch sensors, sensors configured todetect a galvanic skin response (GSR), vision sensors (e.g., imagingdevices capable of detecting visible, infrared, or ultraviolet light,such as cameras), proximity or range sensors (e.g., ultrasonic sensors,lidar, time-of-flight or depth cameras), altitude sensors, attitudesensors (e.g., compasses), pressure sensors (e.g., barometers), humiditysensors, vibration sensors, audio sensors (e.g., microphones), and/orfield sensors (e.g., magnetometers, electromagnetic sensors, radiosensors).

User device 120 may further include one or more devices capable ofemitting a signal into an environment. For instance, the user device mayinclude an emitter along an electromagnetic spectrum (e.g., visiblelight emitter, ultraviolet emitter, infrared emitter). The user devicemay include a laser or any other type of electromagnetic emitter. Theuser device may emit one or more vibrations, such as ultrasonic signals.The user device may emit audible sounds (e.g., from a speaker). The userdevice may emit wireless signals, such as radio signals or other typesof signals. The user device may emit smells and/or tastes (e.g., due tothe release of a chemical). Some of the signals (e.g., audible sound,tactile signals, visual indicators, etc.) may be used to alert a userwhen the air pollution in the user's vicinity exceeds a predeterminedthreshold, and/or to inform the user to take certain corrective actionsto mitigate the impact of air pollution on the user's health.

Wearable device 110 and user device 120 may be operated by one or moreusers consistent with the disclosed embodiments. In some embodiments, auser may be associated with a unique user device and a unique wearabledevice. Alternatively, a user may be associated with a plurality of userdevices and wearable devices. A user as described herein may refer to anindividual or a group of individuals who are seeking to improve theirwellbeing using device 110. For example, a person or a group of personssuffering from allergies may wish to find relief from the allergen. Aperson or a group of persons living in a city with high levels of airpollution may wish to find relief from the air pollution. System 100 candetermine each user's exposure to one or more pollutants, and reducetheir exposure to those pollutants through the wearable devices (e.g.,filtration module).

User device 120 may be configured to receive input from one or moreusers. A user may provide an input to the user device using an inputdevice, for example, a keyboard, a mouse, a touch-screen panel, voicerecognition and/or dictation software, or any combination of the above.The user input may include statements, comments, questions, or answersrelating to a user's air filtration requirements. Different users mayprovide different inputs. The user input may be indicative of the user'shealth conditions. Some of the health conditions may be affected by airpollution.

Server 130 may be one or more server computers configured to perform oneor more operations consistent with the disclosed embodiments. In oneaspect, the server may be implemented as a single computer, throughwhich wearable device 110 and user device 120 are able to communicatewith sensing analysis module 132 and database 150. In some embodiments,the wearable device and/or the user device may communicate with thesensing analysis module directly through the network. In someembodiments, the server may communicate on behalf of the wearable deviceand/or the user device with the sensing analysis module or databasethrough the network. In some embodiments, the server may embody thefunctionality of one or more of sensing analysis modules. In someembodiments, one or more sensing analysis modules may be implementedinside and/or outside of the server. For example, the sensing analysismodules may be software and/or hardware components included with theserver or remote from the server.

In some embodiments, the wearable device and/or the user device may bedirectly connected to the server through a separate link (not shown inFIG. 1A). In certain embodiments, the server may be configured tooperate as a front-end device configured to provide access to one ormore sensing analysis modules consistent with certain disclosedembodiments. The server may, in some embodiments, utilize one or moresensing analysis modules to analyze input data from the wearable deviceand/or user device in order to detect and/or monitor a user's exposureto one or more pollutants, and to provide information (e.g.,recommendations) to assist the user in managing their exposure to thepollutants. The server may also be configured to store, search,retrieve, and/or analyze data and information stored in one or more ofthe databases. The data and information may include raw data and derivedvital signs collected from various sensors (such as global positioningsensors, heart rate monitors, inertial sensors, body temperaturesensors, respiration rate sensors, gait sensors, etc.) on one or moreuser devices, as well as each user's historical exposure to pollutants.While FIG. 1A illustrates the server as a single server, in someembodiments, multiple devices may implement the functionality associatedwith a server.

A server may include a web server, an enterprise server, or any othertype of computer server, and can be computer programmed to acceptrequests (e.g., HTTP, or other protocols that can initiate datatransmission) from a computing device (e.g., user device and/or wearabledevice) and to serve the computing device with requested data. Inaddition, a server can be a broadcasting facility, such as free-to-air,cable, satellite, and other broadcasting facility, for distributingdata. A server may also be a server in a data network (e.g., a cloudcomputing network).

A server may include known computing components, such as one or moreprocessors, one or more memory devices storing software instructionsexecuted by the processor(s), and data. A server can have one or moreprocessors and at least one memory for storing program instructions. Theprocessor(s) can be a single or multiple microprocessors, fieldprogrammable gate arrays (FPGAs), or digital signal processors (DSPs)capable of executing particular sets of instructions. Computer-readableinstructions can be stored on a tangible non-transitorycomputer-readable medium, such as a flexible disk, a hard disk, a CD-ROM(compact disk-read only memory), and MO (magneto-optical), a DVD-ROM(digital versatile disk-read only memory), a DVD RAM (digital versatiledisk-random access memory), or a semiconductor memory. Alternatively,the methods can be implemented in hardware components or combinations ofhardware and software such as, for example, ASICs, special purposecomputers, or general purpose computers.

While FIG. 1A illustrates the server as a single server, in someembodiments, multiple devices may implement the functionality associatedwith server.

Network 140 may be a network that is configured to provide communicationbetween the various components illustrated in FIG. 1A. The network maybe implemented, in some embodiments, as one or more networks thatconnect devices and/or components in the network layout for allowingcommunication between them. For example, wearable device 110, userdevice 120, and sensing analysis module 132 may be in operablecommunication with one another over network 140. Direct communicationsmay be provided between two or more of the above components. The directcommunications may occur without requiring any intermediary device ornetwork. Indirect communications may be provided between two or more ofthe above components. The indirect communications may occur with aid ofone or more intermediary device or network. For instance, indirectcommunications may utilize a telecommunications network. Indirectcommunications may be performed with aid of one or more router,communication tower, satellite, or any other intermediary device ornetwork. Examples of types of communications may include, but are notlimited to: communications via the Internet, Local Area Networks (LANs),Wide Area Networks (WANs), Bluetooth, Near Field Communication (NFC)technologies, networks based on mobile data protocols such as GeneralPacket Radio Services (GPRS), GSM, Enhanced Data GSM Environment (EDGE),3G, 4G, or Long Term Evolution (LTE) protocols, Infra-Red (IR)communication technologies, and/or Wi-Fi, and may be wireless, wired, ora combination thereof. In some embodiments, the network may beimplemented using cell and/or pager networks, satellite, licensed radio,or a combination of licensed and unlicensed radio. The network may bewireless, wired, or a combination thereof.

Wearable device 110, user device 120, server 130, and/or sensinganalysis module 132 may be connected or interconnected to one or moredatabases 150. The databases may be one or more memory devicesconfigured to store data. Additionally, the databases may also, in someembodiments, be implemented as a computer system with a storage device.In one aspect, the databases may be used by components of the networklayout to perform one or more operations consistent with the disclosedembodiments.

In one embodiment, the databases may comprise storage containing avariety of data sets consistent with disclosed embodiments. For example,the databases may include, for example, data collected by varioussensors located on wearable device 110 and/or user device 120. Thedatabases may also include users' preferences, historical exposure toone or more pollutants, and traits associated with exposure to thepollutant, changes and/or improvements in the users' lifestyles thatlead to a reduction in exposure to the pollutant, the users' success atmanaging or overcoming exposure to the pollutant, etc. In someembodiments, the database(s) may include crowd-sourced data comprisingair pollutant exposure information obtained from internet forums andsocial media websites. The Internet forums and social media websites mayinclude personal and/or group blogs, Facebook™, Twitter™, etc.Additionally, in some embodiments, the database(s) may includecrowd-sourced data comprising air pollutant exposure information,whereby this information may be directly input by one or more otherusers into the sensing analysis module(s). The crowd-sourced data maycontain up-to-date or current information on air pollutant exposure,recommendations to reduce or avoid exposure to the pollutant, etc. Thecrowd-sourced data may be provided by other users who have experiencewith trying to reduce their exposure to pollutants.

In certain embodiments, one or more of the databases may be co-locatedwith the server, may be co-located with one another on the network, ormay be located separately from other devices (signified by the dashedline connecting the database(s) to the network). One of ordinary skillwill recognize that the disclosed embodiments are not limited to theconfiguration and/or arrangement of the database(s).

Any of the wearable device, user device, server, sensing analysismodule, and the database may, in some embodiments, be implemented as acomputer system. Additionally, while the network is shown in FIG. 1A asa “central” point for communications between components, the disclosedembodiments are not so limited. For example, one or more components ofthe network layout may be interconnected in a variety of ways, and mayin some embodiments be directly connected to, co-located with, or remotefrom one another, as one of ordinary skill will appreciate.Additionally, while some disclosed embodiments may be implemented on theserver, the disclosed embodiments are not so limited. For instance, insome embodiments, other devices (such as sensing analysis modules(s)and/or database(s)) may be configured to perform one or more of theprocesses and functionalities consistent with the disclosed embodiments,including embodiments described with respect to the server.

Although particular computing devices are illustrated and networksdescribed, it is to be appreciated and understood that other computingdevices and networks can be utilized without departing from the spiritand scope of the embodiments described herein. In addition, one or morecomponents of the network layout may be interconnected in a variety ofways, and may in some embodiments be directly connected to, co-locatedwith, or remote from one another, as one of ordinary skill willappreciate.

The sensing analysis modules(s) may be implemented as one or morecomputers storing instructions that, when executed by processor(s),analyze input data from a user device and/or a wearable device in orderto detect and/or monitor a user's exposure to one or more pollutants,and to provide information (e.g., recommendations) to assist the user inmanaging their exposure to such pollutants. The sensing analysismodules(s) may also be configured to store, search, retrieve, and/oranalyze data and information stored in one or more databases. The dataand information may include raw data collected from various sensors onone or more wearable devices and/or user devices, as well as each user'shistorical behavioral pattern and social interactions relating toexposure to the pollutants. In some embodiments, server 130 may be acomputer in which the sensing analysis module is implemented.

However, in some embodiments, one or more sensing analysis modules(s)132 may be implemented remotely from server 130. For example, a userdevice may send a user input to server 130, and the server may connectto one or more sensing analysis modules(s) 132 over network 140 toretrieve, filter, and analyze data from one or more remotely locateddatabase(s) 150. In other embodiments, the sensing analysis modules(s)may represent software that, when executed by one or more processors,perform processes for analyzing data to determine a user's exposure toone or more pollutants, and to provide information (e.g.,recommendations) to assist the user in reducing their exposure to thepollutants.

A server may access and execute sensing analysis modules(s) to performone or more processes consistent with the disclosed embodiments. Incertain configurations, the sensing analysis modules(s) may be softwarestored in memory accessible by a server (e.g., in memory local to theserver or remote memory accessible over a communication link, such asthe network). Thus, in certain aspects, the sensing analysis modules(s)may be implemented as one or more computers, as software stored on amemory device accessible by the server, or a combination thereof. Forexample, a sensing analysis module (e.g., 132-1) may be a computerexecuting one or more air pollution sensing techniques, and anothersensing analysis module (e.g., 132-2) may be software that, whenexecuted by a server, performs one or more air pollution sensingtechniques.

The air pollutant measurements may be performed at many locations. Forinstance, the measurements may be performed on wearable device. Themeasurements may be performed at a location near to the wearable device,such as by a smartphone or other portable electronic device. Themeasurements may be performed on the cloud-based storage,communications, and analysis system. The air filtration and sensingdevice may be configured to compress measurement data and transmit thecompressed measurement data to the cloud-based storage, communications,and analysis system.

The functions of the sensing analysis module, and its communication withthe wearable device and user device, will be described in detail belowwith reference to FIG. 2A.

The invention as described herein need not be limited to air filtration,but may extend generally to the collection and analysis of respiratoryhealth information to improve users' health and/or well-being. FIG. 1Bshows a schematic of a system comprising one or more air sensing devicesinteracting within a network. The system may comprise the components ofFIG. 1A, such as the wearable device, user device, server, network, anddatabase. In contrast to the system of FIG. 1A, the system of FIG. 1Bmay comprise a wearable device that comprises only a sensing module 114and transmitter 116. The wearable device of FIG. 1B need not include afiltration module, and may be utilized by users who do not require anyair filtration capabilities. For instance, a user who lives in an areawith low pollution and suffers from sleep apnea may utilize the sensingmodule to monitor their breathing during sleep, but may not requirefiltration of the air that they inhale.

FIG. 2A illustrates exemplary components in an air filtration andsensing system. Referring to FIG. 2A, a system 200 may comprise awearable device 110, a user device 120, and a sensing analysis module132. As previously described, the sensing analysis module may beimplemented inside and/or outside of a server. For example, the sensinganalysis module may be software and/or hardware components included witha server, or remote from the server. In some embodiments, the sensinganalysis module (or one or more functions of the sensing analysismodule) may be implemented on the wearable device. Alternatively, thewearable device, user device, and/or server may be configured to performdifferent functions of the sensing analysis module. Optionally, one ormore functions of the sensing analysis module may be duplicated acrossthe wearable device, user device, and/or server.

In the example of FIG. 2A, user device 120 may comprise at least onesensor 122. The sensor 122 may include location sensors (e.g., GPSreceivers), heart rate monitors, inertial sensors (e.g., accelerometersand gyroscopes), etc. One or more other types of sensors as describedelsewhere herein may be incorporated into the user device.

The user device and/or the wearable device may be configured to provideinput data 136 to the sensing analysis module. The input data maycomprise a user health profile 136 a, pollutant sensing data 136 b,physiological sensing data 136 c, location sensing data 136 d,environmental sensing data 136 e, crowd-sourced pollution data 136 f,weather reports 136 g, etc.

The user health profile may be provided by a user via the user device.The user health profile may incorporate information about a user'smedical conditions, prescribed and/or unprescribed medications,electronic health record data, or any other information that may berelevant to a user's health. The user health profile may be in responseto questions provided by the sensing analysis modules. Examples ofquestions may include whether the user has certain health concerns suchas allergies and an estimate of the levels of pollutants that the userhas been exposed to in the recent past. The user's responses to thosequestions may be used to supplement the pollution sensing data topredict where/when the user is likely to be exposed to the pollutants.This information obtained from the user input can be analyzed usingmachine learning processes.

In some cases, the user health profile may be continuously updated inresponse to dynamically changing information provided by the user orobtained by the sensing module. For instance, the user health profilemay initially comprise a baseline profile. The baseline profile mayspecify a user's health profile at an initial point in time. As timeelapses, the user may modify elements of their health profile, such asby providing updated information about their health concerns. In othercases, the sensing module may note changes in the user's health profile,such as by sensing a change in the composition of air exhaled by theuser. Such changes may be compared against the baseline and used toproduce an updated user profile. In some cases, the user profile may becontinuously updated in response to new information provided by the useror obtained by the sensing module. In some cases, “big data” techniquesmay be utilized to continuously update the user profile.

The pollutant sensing data may comprise raw data collected by one ormore pollution sensors on the wearable device, as described herein. Thepollutant sensing data may include, for example, the types of pollutantsin the inhaled air present in the vicinity of the user, as well as thelevel of those detected pollutants. The pollutant sensing data may bestored in memory located on the wearable device, user device, and/orserver. In some embodiments, the pollutant sensing data may be stored inone or more databases. The databases may be located on the server,wearable device, and/or user device. Alternatively, the databases may belocated remotely from the server, wearable device, and/or user device.

The physiological sensing data may comprise data collected by one ormore physiological sensors on the wearable device or user device. Forinstance, the physiological sensing data may comprise one or moremeasurements of a user's heart rate, breathing rate, respiratorybehavior, blood pressure, glucose level, and/or any other physiologicaldata.

The location sensing data may be determined by a location sensor (e.g.,GPS receiver) on the wearable device and/or the user device. The userlocation may be used to determine places where the user is exposed topollutants or is likely to be exposed to pollutants. The user locationmay also be used to supplement the pollution sensing data to determinethe probability of future exposure to the pollutants. The sensinganalysis module can be configured to map the pollutant sensing data tothe detected locations.

The environmental sensing data may comprise data collected by one ormore environmental sensors. The environmental sensing data may compriseinformation obtained from sources that track air pollutant levels, suchas the National Weather Service (NWS) or National Oceanic andAtmospheric Administration (NOAA). The environmental sensing data canprovide various types of environmental information. For example, thesensor data may be indicative of an environment type, such as an indoorenvironment, outdoor environment, low altitude environment, or highaltitude environment. The sensor data may also provide informationregarding current environmental conditions, including weather (e.g.,clear, rainy, snowing), visibility conditions, wind speed, time of day,and so on. Furthermore, the environmental information collected by thesensors may include information regarding the objects in theenvironment, such as the number, density, geometry, and/or spatialdisposition of objects in the environment. The amount of air pollutionmay be affected by the environmental type. For example, a location thatis situated in a valley with low winds and a large number of factoriesmay have higher air pollution compared to another location that is closeto the sea with good air circulation.

The crowd-sourced information may comprise information relevant todetermining a user's exposure to air pollutants. For instance, thecrowd-sourced information may comprise information about current airpollutant levels at one or more locations, predicted future airpollutant levels at one or more locations, or any other informationrelevant to determining the user's exposure to air pollutants. Thecrowd-sourced information may comprise information obtained fromwebsites or applications, such as newsfeeds, social media websites orapplications. The crowd-sourced information may comprise informationobtained from other devices utilized by other users.

The weather reports may comprise information obtained from local ornetwork newscasts.

FIG. 2B illustrates exemplary components in an air sensing system. Thesystem may comprise all of the components of FIG. 2A. In contrast to thesystem of FIG. 2A, the system of FIG. 2B may comprise a wearable devicethat comprises only a sensing module 114 and transmitter 116. Thewearable device of FIG. 2B need not include a filtration module, and maybe utilized by users who do not require any air filtration capabilities.For instance, a user who lives in an area with low pollution and suffersfrom sleep apnea may utilize the sensing module to monitor theirbreathing but need not require filtration of the air that they inhale.

FIG. 3 illustrates the communication between a wearable air filtrationand sensing device, one or more user devices, and a sensing analysismodule, in accordance with some embodiments. The wearable device 110 maybe worn within the user's nasal passages or over the user's mouth and/ornose, as described herein. The wearable device may be communicativelycoupled to user devices 120-1 and/or 120-2. The user device 120-1 may bea mobile device carried by the user, and may include one or more sensorssuch as cameras, microphones, accelerometers, gyroscopes, compasses,GPS, etc. The user device 120-2 may be a wrist-wearable device such as asmartwatch or wristband, which may include one or more sensors formeasuring body temperature, heart rate, motion of the user, etc. Thewearable device 110 and user devices 120-1 and/or 120-2 may becommunicatively coupled to the sensing analysis module 132. The sensinganalysis module may be an app or other program held in memory on themobile device and/or wrist-wearable device. The sensing analysis modulemay be peripheral hardware components communicatively coupled to themobile device and/or wrist-wearable device. The sensing analysis modulemay be configured to receive input data from the various devices 110,120-1 and 120-2, as described elsewhere herein.

FIG. 4A shows an air filtration and sensing device worn inside of auser's nasal passage. The air filtration and sensing device 110 maycomprise an intranasal device worn inside the user's nasal passages. Theintranasal device may be worn entirely within the user's nasal passages.The intranasal device may be worn partially within the user's nasalpassages. The filtration module 112 may intercept natural airflow takeninto the user's nostrils during inhalation. The sensing module 114 mayintercept natural airflow expelled from the user's nostrils duringexhalation.

FIG. 4B shows an air filtration and sensing device worn over a user'snose and mouth. Unlike FIG. 4A, the air filtrations and sensing device110 in FIG. 4B may comprise a face mask device worn over the user's noseand mouth. The filtration module 112 may intercept natural airflow takeninto the user's nostrils or mouth during inhalation. The sensing module114 may intercept natural airflow expelled from the user's nostrils ormouth during exhalation.

FIG. 5A shows a front view of an intranasal air filtration and sensingdevice that is worn substantially within a user's nasal passage. Theintranasal device 110-1 may be worn such that a certain volume of thedevice (e.g., greater than 90%) is located within a user's nasalpassage. FIG. 5B shows a side view of the intranasal air filtration andsensing device of FIG. 5A. FIG. 5C shows a front view of an intranasalair filtration and sensing device worn partially within a user's nasalpassage. The intranasal device 110-2 may be worn such that greater than10%, greater than 20%, greater than 30%, greater than 40%, greater than50%, greater than 60%, greater than 70%, or greater than 80% of thevolume of the device is located within a user's nasal passage. FIG. 5Dshows a side view of the intranasal air filtration and sensing device ofFIG. 5C.

FIG. 6A shows a schematic of a cartridge-based intranasal air filtrationand sensing device 110 worn within a user's nasal passageway. FIG. 6Bshows a magnified view of the device 110 of FIG. 6A. The intranasal airfiltration and sensing device may comprise an intranasal filtrationmodule 112, as described herein. The intranasal filtration module maycomprise a cartridge holder 600 and a filter cartridge 602. Thecartridge holder may be configured to receive and couple to the filtercartridge, in order to hold the filter cartridge in place within theintranasal filtration in module. The cartridge holder may be configuredto reversibly couple to the filter cartridge in order to allow differentfilter cartridges to be utilized at different moments in time. Thecartridge holder may be configured to allow the filter cartridge to snapin and out of the cartridge holder.

In some cases, the cartridge filter may be configured to beinterchanged. The cartridge filter may be mounted onto the cartridgeholder using a quick release mechanism. The cartridge filter may beconfigured to be interchanged and/or mounted onto the cartridge holderwithout using tools. The cartridge filter and/or cartridge holder maycomprise security features, such as mechanical and/or electrical keys orinterlocks.

The use of a cartridge-based filtration element may allow the usefulperformance lifetime of the filtration module to be extended. Airfilters may clog as pollutants accumulate, requiring the filtrationelements to be periodically replaced. The use of an easy-to-replacecartridge format may address the need to replace filter elements. Theuse of a cartridge format may have the additional advantage of allowinga filter with a varying and potentially highly complex internalcomposition to be easily snapped in and out of the cartridge holder as asingle monolithic object.

The use of a cartridge-based filtration module may also allow thefiltration element to be customized for a given user's needs orpreferences. For instance, different filtration properties may berequired for different users, such as a physician, a woodworker exposedto saw dust, an expectant mother in Beijing, an asthmatic, a personrecovering from a medical intervention, and a person with sleep apnea.In general, different users will have different preferences, rangingfrom zero filtration (no cartridge) to maximum filtration. The physicianmay seek to maximize protection to airborne viruses and bacteria. Thewoodworker generating wood dust may prefer filter cartridges that removedust and large particulate matter. An expectant mother in Beijing mayseek filter cartridges that best protect her and her fetus from PM2.5particulate matter and carbon monoxide. The athlete may prefer a filtercartridge that provides the highest possible airflow through thefiltration element. A person recovering from a medical intervention athome, having a medical condition, or wishing to collect data about theirbreathing may desire zero filtration, using the device to measure,monitor, and report respiratory rate, volume, and other vital signs.Similarly, a person suffering from sleep apnea may utilize the devicesolely for the purpose of measuring, monitoring, and reportinginformation about their breathing during sleep. In some cases, a usermay utilize the sensing module to detect other exhaled compounds, suchas metabolic end-products or other volatile organic compounds. In somecases, a user may wish to utilize the sensing module to detect changesin exhaled compounds which may relate to their participation in amedical treatment program, such as the use of therapeutic medications.The use of a removable and replaceable cartridge-based filtration modulemay allow each of these users to utilize a filtration cartridge havingan internal composition customized for their particular needs, which maychange over time or be determined by their location, activity, andhealth status.

FIG. 7A shows a schematic of a cartridge-based intranasal air filtrationdevice comprising a plurality of filtration layers. The intranasal airfiltration and sensing device may comprise an intranasal filtrationmodule 112, as described herein. The intranasal filtration module maycomprise a cartridge holder 600 and a filter cartridge 602. The filtercartridge may comprise one or more layers. The filter cartridge maycomprise a first layer 602 a, a second layer 602 b, and a third layer602 c. The filter cartridge may comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,or more than 10 layers.

The layers may contain a plurality of components in varying amounts andthicknesses. The overall composition of the cartridges may be formulatedto address specific pollutants, pollutant levels, and user preferences.The internal composition and structure of the filtration elementsdetermines their overall filtration characteristics and associatedparameters, such as the inhalation resistance, exhalation resistance,moisture and heat experienced by the user when wearing the device.

Referring to FIG. 7B, the layers may be arranged in order of decreasingsize of the target pollutant, with the largest pollutants being excludedat the earliest possible location within the filter. For instance, thefirst layer 602 a may comprise a coarse filtration element, such as ametal mesh or a fiberglass mesh, to filter relatively large pollutantssuch as pollen, dander, PM10, or dust. The second layer 602 b maycomprise a less coarse filtration element, such as a glass fiber mesh, ananofibrilated material, or an electrostatic capture device, to filtersmaller pollutants such as PM2.5. The third layer 602 c may comprise afine filtration element, such as an activated carbon dopant added to asubstrate, to filter gasses such as CO, or NOR. The third layer may beconfigured to filter gasses and other pollutants with activated carbonwhose pore volume distribution (and therefore the relative fractions ofmicro-, meso-, and macro-pores) has been matched to the expected,predicted, or known chemical characteristics. Accordingly, the layersmay comprise a coarse filtration element, a less coarse filtrationelement, or a fine filtration element. In some embodiments, elementswith varying degrees of filtration capabilities can be fabricated into asingle layer, with increasing and/or decreasing levels of granularity.

FIG. 8 shows a flowchart of a method of providing a user with acustomized air filtration device. The method 800 may comprise providingvarious input data (e.g., location, season, crowd-sourced data, userhealth information, etc.) to a sensing analysis module (step 805). Next,the sensing analysis module can determine an optimal filter for the userbased on the input data (step 850). The filter can be fabricated for theuser, and subsequently shipped to the user, for example by a third partyentity (manufacturer).

The input data may include a user's location 810. Providing the locationmay allow information about the locality to be utilized in determiningan optimal filter for the user. For instance, measurements of theconcentrations of a variety of air pollutants (such as plant pollen, CO,NOx, PM2.5, PM10, or other pollutants) from fixed environmental sensorsat the location may be utilized to determine which filtration layers toinclude in a filtration cartridge to be utilized by the user.

The input data may include information about the current season 820.Providing information about the season (e.g., which season of the year,beginning of the season, mid or end of season) may allow temporalinformation to be utilized in determining an optimal filter for theuser. For instance, measurements of the concentrations of a variety ofair pollutants (such as plant pollen, CO, NOx, PM2.5, PM10, or otherpollutants) from fixed environmental sensors at the location duringdifferent seasons may be utilized to determine which filtration layersto include in a filtration cartridge to be utilized by the user. In thismanner, different optimal filters can be utilized for different seasons.For instance, an optimal filter for spring may include layers designedto filter pollen or other spring-time allergens, while an optimal filterfor winter may not require these layers.

The input data may also include crowd-sourced information 830. Thecrowd-sourced information may comprise information relevant todetermining a user's exposure to air pollutants. For instance, thecrowd-source information may comprise information about current airpollutant levels at one or more locations, predicted future airpollutant levels at one or more locations, or any other informationrelevant to determining the user's exposure to air pollutants. Thecrowd-sourced information may comprise information obtained fromwebsites or applications, such as newsfeeds, social media websites orapplications. The crowd-sourced information may comprise informationobtained from other devices utilized by other users. The crowd-sourcedinformation may comprise information obtained from local or networknewscasts. The crowd-sourced information may comprise informationobtained from sources that track air pollutant levels, such as theNational Weather Service (NWS) and/or National Oceanic and AtmosphericAdministration (NOAA). Additionally or alternatively, the crowd-sourcedinformation may comprise other sources of information such ashealth-related web sites (such as patientslikeme) and search engines,which can provide information about trending web searches (such as thenumber of people searching for ‘flu-like symptoms’ in a particulargeographic location).

The input data may also include user health information 840. The userhealth information can be used to determine an optimal filter for theuser. For instance, if the user has an allergy to a particular substance(such as pollen) in the atmosphere, such information may be utilized toinclude a filtration layer to filter that allergen. Likewise, if theuser has sleep apnea and wishes to monitor and record his or herbreathing at night, the user may wish to forgo any kind of filtrationand use the device only for health sensing and monitoring.

In step 850, an optimal filter for the user is determined by the sensinganalysis module. The optimal filter may be determined by considering oneor more pieces of the input data provided in step 805. The optimalfilter may be determined from additional pieces of information, such asa user's personal preferences, as described herein.

The filter can be fabricated using any fabrication methods. Forinstance, the filter may be fabricated utilizing laser fabricationmethods, such as laser cutting, laser perforation, and/or laser spotwelding. The filter may be fabricated utilizing additive manufacturingtechniques, such as 3D printing. The filter may be fabricated utilizingany rapid fabrication methods as are known to one skilled in the art.

A person of ordinary skill in the art will recognize many variations,alterations and adaptations based on the disclosure provided herein. Forexample, additional steps may be added as appropriate. Some of the stepsmay comprise sub-steps. Some of the steps may be automated (e.g.,autonomous pollutant and/or environmental sensing), whereas some of thesteps may be manual (e.g., requiring manual input or responses from auser). The systems and methods as described herein may comprise one ormore instructions to perform at least a portion of one or more steps ofmethod 800.

The capability to manufacture a practically unlimited diversity ofchemically and physically distinct filter cartridges may result inbetter health outcomes and better protection of people from airpollutants. Additionally, rapid fabrication technologies may be combinedwith an integrated sensing, fluid dynamics, and analytics infrastructurethat allows geographically-, temporally-, and user-optimized filterelements to be rapidly formulated.

Personalized filter formulation and rapid manufacturing may onlypartially address a user's filtration needs. For instance, an athlete inBeijing in the summer may seek a different level of protection comparedto a pregnant woman in the same location. The athlete may wish tominimize the filtration module's resistance to respiration, a filterelement consisting solely of a porous metal mesh with a mesh size of 3microns. By contrast, the expectant woman may wish to maximizeprotection from all known pollutants, encompassing dust and gasses suchas carbon monoxide, pointing to a much more complex multi-element filterwith activated carbon, metal meshes, and woven glass fibers. Such afilter might be optimal for the expectant woman, but have an intolerablyhigh resistance to respiration for an athlete.

Therefore, rapid filter formulation and rapid filter manufacturing maybe combined with a user interface software that allows the user toindicate personal choices about their current preferences regardingtheir preferred tradeoff between comfort and desired protection levels.For instance, the software may allow the user to drag a slider from left(red) to right (green) to indicate their protection preference. The userinterface element may be labeled with words that clarify the choice theuser is making concerning the ease of breathing versus protection. Forinstance, the software may include such wording as ‘best protection’ onone end of the slider element and ‘easiest breathing’ on the other.

The software may use real-time sensor data from a miniaturized airpollution sensor worn by a user to suggest changes in personal habits orchanges in filter cartridge composition to reduce exposure. The softwareback-end may track exposure and activity to predict when a user willrequire a new shipment of filter cartridges, and will ask and/or remindthe user to reorder filter cartridges.

In some implementations, a sensor within or near the filtration systemmay process sensing data locally and/or transmit the sensing data to thesensing analysis module. The sensing analysis module can providefeedback to the user and allow the user to monitor pollution levels andthe performance of their filter, based on the sensing data. Relevantevents and changes may be signaled to the user via a buzzer, sound, orlight signals.

Data from a local sensor and data from remote and/or crowd sensors maybe integrated by a central computer (e.g., implemented as a sensinganalysis module) allowing information to be provided to the user, suchas pollution-minimizing walking/traffic routing information and localpollution levels. Pollution information and associated data (such as anoptimized exposure-minimizing route) may be provided to the user,allowing the user to change their actions and choices, such as the typeof filter they wish to use in their filtration system.

For instance, an athlete with a “high-flow” filter cartridge may wish tobe warned if the local ozone levels exceed a preset level, allowing themto stop their exercise or otherwise respond to that environmentalchange, such as by snapping a different type of filter cartridge into aflexible carrier structure that sits stably in their nose.

The need to select between better filtration and increased airflow maybe partially mitigated by incorporating additional elements to increasethe airflow while maintaining a high level of filtration performance.For instance, the air filtration and sensing device may comprise afiltration element utilizing micro- or nano-fibrous elements, a dilationstructure to open the nasal passage, or a filter cartridge that changesposition within the nasal passages during inhalation and exhalation.

FIG. 9A shows a schematic of a cartridge-based intranasal air filtrationdevice comprising a plurality of filtration elements, during a period inwhich a user is inhaling. The filtration module 112 may comprise aplurality of fibrous elements in a first configuration 900 a duringinhalation. The filtration elements may comprise micro-fibrous elements.The filtration elements may comprise nano-fibrous elements. Thefiltration elements may comprise a mesh, such as a fine metal mesh. Thefiltration elements may comprise one or more membranes. The filtrationelements may comprise one or more granulated chemicals. The filtrationelements may be shaped like the valves of the human heart. Duringinhalation, the filtration elements may be in a “closed” configurationand arranged in a tight grouping with little space located betweenadjacent elements. In this manner, the filtration elements may providefiltration of air during inhalation.

FIG. 9B shows a schematic of a cartridge-based intranasal air filtrationdevice comprising a plurality of filtration elements, during a period inwhich a user is exhaling. The filtration module 112 may comprise aplurality of filtration elements in a second configuration 900 b duringexhalation. During inhalation, the filtration elements may be in an“open” configuration and arranged in a loose grouping with little spacelocated between adjacent elements. In the manner, the filtrationelements may have a reduced resistance to exhalation, when extensivefiltration of the air may not be necessary.

FIG. 10A shows a schematic of a cartridge-based intranasal airfiltration and sensing device comprising a dilation structure to openthe nasal passage for increased airflow. The filtration module 112 maycomprise a dilation structure 1000 that dilates natural constrictionsthat are located deep within the nasal cavity and that naturallyincrease the nasal passages' resistance to airflow. The dilationstructure may dilate any structure within the nose that would otherwiserestrict the flow of air through the nasal passages. For instance, thedilation structure may dilate the aperture defined by the nasal septumand the base of the Inferior Turbinate, which may be a critical chokepoint for air in the nasal passages. This aperture can have a lateraldimension of less than 3 mm, creating a high drag choke-point for theflowing air.

FIG. 10B shows a magnified view of the dilation structure of FIG. 10A.The dilation structure may comprise a flexible elastic mesh. Theflexible elastic mesh may be located at least 1 mm, at least 2 mm, atleast 3 mm, at least 4 mm, at least 5 mm, at least 6 mm, at least 7 mm,at least 8 mm, at least 9 mm, at least 10 mm, at least 11 mm, at least12 mm, at least 13 mm, at least 14 mm, or at least 15 mm deep within thenasal cavity as measured from the base of the nostril. The flexibleelastic mesh may dilate this natural construction, yielding a reductionof air resistance.

FIG. 11A shows a cartridge-based air filtration device in a positionallowing increased filtration and reduced airflow during a period inwhich a user is inhaling. The filtration module 112 may comprise acartridge holder 600 and a cartridge 602, as described herein. Thecartridge may be movable, such that its position within the cartridgeholder may change over time depending on which part of the breathingcycle the user is undergoing. During inhalation, the cartridge may be ina first position 602 a in which the cartridge is located with relativelylittle space between the cartridge holder and the cartridge. Therelatively small amount of space between the cartridge holder and thecartridge may force air through the cartridge during inhalation,allowing filtration of the incoming air.

FIG. 11B shows a cartridge-based air filtration device in a positionallowing reduced filtration and increased airflow during a period inwhich a user is exhaling. The filtration module 112 may comprise acartridge holder 600 and a cartridge 602, as described herein. Duringexhalation, the cartridge may be in a second position 602 b in which thecartridge is located with a relatively large amount of space between thecartridge holder and the cartridge. The relatively large amount of spacebetween the cartridge holder and the cartridge may allow air to passaround the cartridge, thereby decreasing the resistance to airflow.

The provision of alternative air exit paths may have other benefitsbeyond making it easier to exhale. For example, the exhaled air may bemoist and carry this moisture into the filter, where it can accumulateand potentially degrade filtration. By providing alternative exit pathsfor the exhaled air, the air may be able to leave the filtration systemwithout needing to pass through the filter element, thereby extendingthe lifetime and/or performance of the filtration module.

The filtration module may include a shell allowing customization of thefit within a user's nasal passages. The shell may be made of a plasticmaterial. The shell may be fabricated with rapid fabricationtechnologies such as 3D printing. Slight imperfections between theplastic shell and the nasal anatomy may be filled with materials thatallow the final shape to be molded after the device has been provided tothe user. For instance, the gap-filling material may consist of athermoplastic polymer. The thermoplastic polymer may have a meltingpoint of between 45 and 85 degrees Celsius, 45 and 80 degrees Celsius,50 and 75 degrees Celsius, 50 and 70 degrees Celsius, 55 and 65 degreesCelsius, or 55 and 60 degrees Celsius. The melting point may be chosento be compatible with the thermosensitivity of tissues with the humannose, which may sharply limit the temperature of a thermoplasticmaterial that can be inserted into the human nose without causingdiscomfort. The thermoplastic material may contain a temperaturesensitive dye, so that the user can confidently and reliably determinethe correct temperature of the thermoplastic material to maximizeshaping capability and comfort while forming the material and waitingfor it to set.

The filtration module may include one or more of the air resistancereduction strategies described herein along with a filter element. Thefilter element may comprise a low-resistance nano-structured ornano-fibrilated polymer mesh that can provide good particle filtrationperformance with reduced air resistance. For instance, the materials mayallow pressure drops that are lower by at least a factor of two comparedto conventional air filter materials.

The sensing module may comprise one or more sensor elements. The sensorelements may comprise one or more air pollution sensors capable ofdetecting one or more air pollutants such as gasses (e.g. CO, NOx,ozone, or sulfur-containing compounds), particulate matter (e.g. soot,dust, PM2.5, or PM10), or biological particles (e.g. pollen, bacteria,or viruses). The air pollution sensors may comprise optical sensorsbased on the reflection, transmission, absorption, or scattering orlight. The air pollution sensors may comprise optoelectronic sensors.The air pollution sensors may comprise chemical reactivity sensors. Theair pollution sensors may comprise mass sensors based on changes invibrational characteristics.

In addition to air pollution sensors, the sensing module may compriseone or more complementary sensors providing complementary information.The complementary sensors may comprise one or more global positioningsystem (GPS) sensors for detecting a location of the air filtration andsensing device. The complementary sensors may comprise one or moreinertial sensors such as accelerometers or gyroscopes for detecting anorientation of the air filtration and sensing device. The complementarysensors may comprise one or more altitude sensors such as a barometerfor measuring an altitude of the air filtration and sensing device. Thecomplementary sensors may comprise one or more external temperature,humidity, air pressure, or wind speed sensors for measuring atemperature, humidity, air pressure, or wind speed, respectively, in theenvironment of the air filtration and sensing device. The complementarysensors may comprise one or more heart rate monitors for measuring aheart rate of a user. The complementary sensors may comprise one or moreskin temperature sensors for detecting a skin temperature of a user. Thecomplementary sensors may comprise one or more galvanic skin responsesensors for determining electrical characteristics of the skin of auser. The complementary sensors may comprise one or more blood oxygensaturation sensors. The complementary sensors may comprise one or moremetabolic sensors for measuring metabolic function of a user. Thecomplementary sensors may comprise one or more capacitive sensorsresponding to a touch of a user. In some cases, the sensors may comprisemicroelectromechanical systems (MEMS) or nanoelectromechanical systems(NEMS) sensors. In some cases, the MEMS or NEMS sensors can beconfigured to be removable from the sensing module. For instance, thesensing module can be configured to be allow MEMS or NEMS sensors to bereplaced with other sensors based on user or environmentalcircumstances.

FIG. 12 shows a schematic of an air sensing device utilizing an opticaldetection scheme. The sensing module 114 may comprise an opticaldetector utilizing scattering of light to detect one or more airpollutants. The optical detector may comprise a light source 1202,collimating optics 1204, light collecting optics 1206, and a detector1208. The light source may comprise a broadband light source such as alight emitting diode (LED). The light source may comprise asemi-monochromatic light source such as a laser. The light source maycomprise a continuous wave laser or a pulsed laser. The light source maycomprise a gas (e.g. carbon dioxide or helium-nitrogen) laser, a dyelaser, a solid-state laser (e.g. a Nd:YAG laser), a fiber laser (e.g. arare-earth doped fiber laser), a semiconductor laser (e.g. a verticalcavity surface emitting laser), or any other laser as is known to onehaving skill in the art. The light source may comprise multiple lightsources.

The light source directs light to the collimating optics. Thecollimating optics direct light from the light source to a pollutant1200 under investigation by the optical sensor. The collimating opticsmay collimate the light as it is passed to the pollutant underinvestigation by the optical sensor. The collimating optics may compriseone or more lenses. The collimating optics may comprise one or moremicrolenses. Upon interaction with the pollutant, light is scatteredtoward the light collection optics.

The light collection optics direct light scattered from the pollutant tothe detector. The light collection optics may comprise focusing opticswhich focus the scattered light as it is passed to the detector. Thelight collection optics may comprise one or more lenses. The lightcollection optics may comprise one or more microlenses. The lightcollection optics may comprise one or more ball lenses. The lightcollection optics may comprise one or more mirrors. The light collectionoptics may comprise one or more micromirrors. The light collectionoptics may comprise one or more parabolic mirrors. The light collectionoptics may comprise one or more parabolic concentrators. The lightcollection optics may comprise one or more compound parabolicconcentrators.

The detector registers an optical signal that may be indicative of thepresence of a pollutant. The detector may comprise one or morephotodiodes, one or more avalanche photodiodes, one or morecharge-coupled device (CCD) cameras, or one or more complementary metaloxide semiconductor (CMOS) cameras. The detector may comprise any otherdetector as is known to one having skill in the art. The detector may becoupled to one or more lock-in amplifiers allowing lock-in detection ofthe optical signal.

The optical detector may comprise one or more additional opticalelements that may minimize the aspect ratio or size of the opticalsensor by folding the optical path into a more compact space. Forinstance, the additional optical elements may allow the optical path tobe converted into a U-shaped optical path.

FIG. 13A shows a schematic for an air sensing device utilizing anoptical detection scheme with a reduced optical path length comprisingone or more mirrors. The optical sensor 114 described herein maycomprise the light source 1202, collimating optics 1204, lightcollection optics 1206, and detector 1208. In addition, the opticalsensor may comprise mirrors 1203, 1205, and 1207. The mirrors mayproduce a U-shaped optical path of light through the optical sensor. Themirrors may comprise micromirrors.

FIG. 13B shows a schematic for an air sensing device utilizing anoptical detection scheme with a reduced optical path length comprisingone or more polarizing elements. The optical sensor 114 described hereinmay comprise the light source 1202, collimating optics 1204, lightcollection optics 1206, and detector 1208. In addition, the opticalsensor may comprise one or more mirrors 1203 and 1207, and one or morepolarizing elements 1209a and 1209b. The mirrors may comprisemicromirrors. The polarizing elements may comprise two polarizingelements. The polarizing elements may comprise a pair of crossedpolarizers. The crossed polarizers may minimize the entry of light thathas not been scattered by a pollutant into the detector.

The sensing module may comprise one or more air pollution sensorsutilizing a non-optical detection principle. For instance, the sensingmodule may comprise air pollution detectors based on quartz crystalmicrobalances or other resonators for mass measurement. The sensingmodule may comprise air pollution detectors that are placed into contactwith air that naturally moves through a human airway due to respiration.The sensors may be arranged in a variety of geometries within thechannel or on the surface of the channel such as in a ring architectureor a staggered spiral, to avoid sensor-to-sensor interference. Althoughthe figure shows the sensor(s) placed within a cylindrical channel, thespecific shape of the structure over which (or through which) the airmoves can vary widely (e.g. a flat surface, a cylindrical channel, or anotherwise curved surface).

FIG. 14A shows a schematic for an air pollution sensing devicecomprising a plurality of sensing elements arranged in a linear manner.The sensing module 114 may comprise one or more sensors 114 a, 114 b,114 c, and 114 d arranged in a linear manner across a dimension of thesensing module.

FIG. 14B shows a schematic for an air pollution sensing devicecomprising a plurality of sensing elements arranged in a staggeredmanner. The sensing module 114 may comprise one or more sensors 114 a,114 b, 114 c, and 114 d arranged in a staggered manner across thesensing module. For instance, the sensors may be arranged in a spiral orin a ring. The use of a staggered geometry may minimize interferencebetween the sensors. For example, a chemical sensor that locally impedesairflow could impair the performance of a pressure sensor locateddownstream from the chemical sensor. Likewise, a heated MEMS sensorcould bias the performance of a temperature sensor located downstreamfrom the heated MEMS sensor. These forms of sensor interference may bereduced by staggering the sensors in a spiral path relative to theairflow.

The sensing module may contain more than one sensor, such that otherparameters of the moving air (e.g. pressure, velocity, temperature, andhumidity) are sampled. Measurement of these parameters may facilitatethe accurate calibration and normalization of gas concentration, airquality, and/or particulate matter.

For instance, measurement of the velocity of the air flowing through achannel of defined diameter may allow the flux of air into and out ofthe body to be estimated. This in turn may allow the exposure to an airpollutant (e.g. particulate matter) to be calculated. Such a calculationmay involve the signal from an air pollution sensor, the signal from anair velocity sensor, and the cross-sectional area of the channel throughwhich the air is entering the human body. For example, a measured airvelocity of 180 cm/s may be multiplied by the cross-sectional area of acylindrical channel with a radius of 1 cm to yield a volume of 570 cm³of air moving through this channel per second. A particulate mattersensor may measure a concentration of 0.6 mg/m³. This concentration maybe multiplied by the volumetric flow rate to conclude that the wearerhas inhaled 0.0003 mg of particulate matter per second. Theinstantaneous particular matter exposure may be integrated to determinea total exposure of the user to particulate matter during a particularperiod of time.

The air velocity may be determined from a measurement of the airpressure using a pressure sensor. The measurement of the air pressureinside a channel of a defined diameter may allow the flux of air intoand out of the body to be estimated utilizing Bernoulli's equation. Theaddition of a temperature reading from a temperature sensor may be usedto correct the raw pressure signal and obtain a corrected air velocity.

The sensing module may be configured to operate with reduced powerconsumption and to operate in sync with a user's breathing cycle. Thesensing module may be coupled to hardware or software that utilizespredictive algorithms to monitor airway pressure and flow in a user'snasal passages. Such respiratory information may be utilized toadaptively gate the timing of gas sensing windows to allow sampling byone or more air pollution sensors only when a user is inhaling orexhaling.

The sensing module may be configured to use information from a pressuresensor to predict when the next exhalation cycle will be and tooptimally gate the gas sensing window based on the prediction. Forexample, an energy- and information-efficient sampling procedure may beto gate a nondispersive infrared (NDIR) sensing cycle ˜600 ms afteronset of exhalation. As the wearer changes their respiratory rate, thesensing module may change the gating such that the gas sensing eventalways occurs at the same time relative to onset of exhalation.

The sensing module may use information from a pressure sensor toanticipate when the next exhalation cycle will be, and uses thatprediction to perform a pair of measurements, one occurring duringinhalation, and the other occurring during exhalation. By comparingthese two numbers, and performing a differential measurement that isoptimally and adaptively synchronized to human breathing, the sensingmodule may be able to provide robust estimates of the exhaled gascomposition regardless of the potentially varying gas composition of theinhaled air.

The sensing module may use information from a pressure sensor toanticipate when the next exhalation cycle will be, and use thatprediction to sample the exhaled breath at different delay timingsrelative to the onset of exhalation. As a person exhales, the aircontained in the lung is forced out of the body, with different airvolumes coming from different regions within the human airway. Forexample, air leaving the human body about 100 ms after onset ofexhalation may come mostly from the nasal cavity and upper respiratorytract. By contrast, air leaving the nose about 800 ms after onset ofexhalation may come mostly from the nasal cavity and lower respiratorytrack. If the sensing module monitors respiration via a pressure sensor,the sensing module may be able to use that information to obtainmultiple samples of the exhaled air, and therefore differentially probeair coming from different regions of the human airways.

The sensing module may be partially or entirely powered by a powergenerating module capable of converting mechanical energy from breathinginto electrical energy. The power generating module may comprise one ormore power generating elements configured to fit within or near airwaysof the human body. The power generating elements may intercept some orall of the air moving through the human airway. The power generatingelements may be configured to fit within the nasal cavity.

FIG. 15A shows a schematic for a device capable of converting energyfrom breathing to electrical energy comprising a piezoelectric elementattached to flexible vanes 1504 of a one-way valve 1502, during a periodin which a user is inhaling The power generating module may comprise oneor more piezoelectric elements bonded to the flexible vanes of a one-wayair valve. During inhalation, the vanes may be in a first configuration1500 a. In this first configuration, the vanes may be configured suchthat the piezoelectric elements are in a stressed configuration andproduce a flow of electric current. The passage of air during inhalationmay maintain the vanes in the first configuration, allowing an electriccurrent to be generated as long as a user is inhaling.

FIG. 15B shows a schematic for a device capable of converting energyfrom breathing to electrical energy comprising a piezoelectric elementattached to flexible vanes 1504 of a one-way valve 1502, during a periodin which a user is exhaling. The power generating module may compriseone or more piezoelectric elements bonded to the flexible vanes of aone-way air valve. During inhalation, the vanes may be in a secondconfiguration 1500 b. In this second configuration, the vanes may beconfigured such that the piezoelectric elements are in an unstressedconfiguration and do not produce a flow of electric current. Generationof the electric current may recommence when the user starts to inhaleand the vanes move into the stressed configuration once again.

The power generating module may be configured to generate electric powerduring exhalation instead of, or in addition to, during exhalation. Forinstance, the one-way valve may be configured to be in a stressedconfiguration during exhalation instead of during inhalation. The powergenerating module may comprise a first one-way valve configured togenerate electric current during inhalation and a second one-way valveconfigured to generate electric current during exhalation in order toharvest energy from both phases of the breathing cycle.

FIG. 15C shows a schematic for a device capable of converting energyfrom breathing to electrical energy comprising a piezoelectric element1508 attached to the surface of an air-carrying tube 1506, during aperiod in which a user is inhaling. The power generating module maycomprise one or more piezoelectric elements bonded to the surface of anair-carrying tube. During inhalation, the tube may be in a firstconfiguration 1500 c. In this first configuration, the tube may beconfigured such that the piezoelectric elements are in a stressedconfiguration and produce a flow of electric current. The passage of airduring inhalation may maintain the tube in the first configuration,allowing an electric current to be generated as long as a user isinhaling.

FIG. 15D shows a schematic for a device capable of converting energyfrom breathing to electrical energy comprising a piezoelectric element1508 attached to the surface of an air-carrying tube 1506, during aperiod in which a user is exhaling. The power generating module maycomprise one or more piezoelectric elements bonded to the surface of anair-carrying tube. During exhalation, the tube may be in a secondconfiguration 1500 d. In this second configuration, the tube may beconfigured such that the piezoelectric elements are in an unstressedconfiguration and do not produce a flow of electric current. Generationof the electric current may recommence when the user starts to inhaleand the tube moves into the stressed configuration once again.

The power generating module may be configured to generate electric powerduring exhalation instead of, or in addition to, during exhalation. Forinstance, the tube may be configured to be in a stressed configurationduring exhalation instead of during inhalation. The power generatingmodule may comprise a first tube configured to generate electric currentduring inhalation and a second tube configured to generate electriccurrent during exhalation in order to harvest energy from both phases ofthe breathing cycle.

Providing natural airflow caused by breathing may obviate the need fordevices capable of forcing air into a sensor. Thus, the power generatingmodule may significantly reduce the amount of power needed to operatethe sensing module. The use of natural airflow may reduce the powerrequirements of the sensing module by more than 0.1 W, 0.2 W, 0.3 W, 0.4W, 0.5 W, 0.6 W, 0.7 W, 0.8 W, 0.9 W, or 1 W compared to a sensorutilizing a fan or a resistive element to move air through the sensor.The reduced power consumption may allow the sensor to operate for asignificantly increased lifetime without the need to supply a newbattery.

The sensing module may be powered by a wireless charging power source.The sensing module may be powered by an inductive charging power source.The sensing module may be powered by a battery. The air filtration andsensing device may comprise a power consumption module. The powerconsumption module may be configured to allow the air filtration andsensing device to switch between a low-power power saving mode and ahigh-power performance mode depending on a user's needs at differentpoints in time.

FIG. 16 shows a flowchart for a method of utilizing data from aplurality of sensors to construct a personalized pollution exposurescore to a user wearing an air filtration and sensing device. The method1600 may comprise the steps of obtaining a PM2.5 measurement, obtaininga PM10 measurement, obtaining a CO measurement, obtaining a humiditymeasurement, obtaining a pollen measurement, obtaining other sensordata, providing user-specific information, integrating and analyzing thesensor data and user-specific information, adjusting sensor parameters,transmitting to a central computer, producing a personalized pollutionscore, and issuing an alert to a user.

In step 1610, a PM2.5 measurement is made. The PM2.5 measurement may bemade by the sensing module utilizing any air pollution sensor asdescribed herein. In step 1612, a PM10 measurement is made. The PM10measurement may be made by the sensing module utilizing any airpollution sensor as described herein. In step 1614, a CO measurement ismade. The CO measurement may be made by the sensing module utilizing anyair pollution sensor as described herein. In step 1616, a humiditymeasurement is made. The humidity measurement may be made by the sensingmodule utilizing any humidity sensor as described herein. In step 1618,a pollen measurement is made. The pollen measurement may be made by thesensing module utilizing any air pollution sensor as described herein.In step 1620, additional sensor measurements are made. The additionalsensor measurements may be made by the sensing module utilizing anysensor as described herein.

One or more of steps 1610, 1612, 1614, 1616, 1618, or 1620 may furthercomprise sensor calibration. For instance, one or more of steps 1610,1612, 1614, 1616, 1618, or 1620 may comprise calibrating a sensoragainst a baseline sensor or baseline reference, checking whether thesensor is operating normally, determining if the sensor is defective orfaulty, and/or correcting for sensor drift, sensor error, or sensorbias. The sensor calibration may be automated. The sensor calibrationmay be performed dynamically.

One or more of steps 1610, 1612, 1614, 1616, 1618, or 1620 may comprisecollecting sensor data. For instance, one or more of steps 1610, 1612,1614, 1616, 1618, or 1620 may comprise setting a sampling rate, samplingfrequency, or accuracy of the sensor.

One or more of steps 1610, 1612, 1614, 1616, 1618, or 1620 may comprisecross-checking an accuracy of the sensor data against other types ofsensor data. For instance, one or more of steps 1610, 1612, 1614, 1616,1618, or 1620 may comprise correlating sensor data from differentsensors within the sensing module, correlating sensor data with externalsensors (e.g. sensors at weather stations), assigning weights to thedata obtained by a sensor based on its accuracy, and/or discardinginaccurate or unreliable sensor data or flagging such sensor data forfurther analysis. One or more of steps 1610, 1612, 1614, 1616, 1618, or1620 may comprise employing statistical analysis procedures (e.g. aMahalanobis distance or Euclidean distance) to determine a sensoraccuracy.

In step 1630, user-specific information is provided. The user-specificinformation may comprise one or more of the user's age, gender,location, height, weight, body mass index (BMI), body compositioninformation (such as body fat content), health status (such as ongoingmedical conditions like allergies, high blood pressure, or other medicaldisorders), and personal preferences as to level of protection desired.The user-specific information may comprise any user-specific informationas may be useful in determining a personalized pollution score, asdescribed herein.

In step 1640, the sensor data and user-specific information areintegrated and analyzed. Step 1640 may comprise sensor fusion ofdifferent sensor data to, for instance, compensate for certain inherentdeficiencies of individual sensors. For instance, step 1640 may compriseapplying one or more filters. The filters may comprise Kalman filters.The filters may comprise higher-order filters. The filters may compriseany filter as is known to one having skill in the art.

The sensor data may be analyzed using a variety of devices in a varietyof locations. For instance, the sensor data may be analyzed on a user'smobile device, such as a user's smartphone, tablet computer, laptopcomputer, or any other portable electronic device. The sensor data maybe analyzed on a user's wearable device, such as a user's smartwatch.The sensor data may be analyzed at a remote server. The remote servermay further perform aggregation of sensor data for multiple users withinthe same geographic location or across different geographic locations.The aggregated sensor data may allow for the creation of crowd-sourcedpollution data in a variety of geographic locations.

In some embodiments, step 1640 may further comprise the compressionand/or storage of raw or analyzed sensor data. The compressed sensordata may be compressed and/or stored on a user's mobile device, such asa user's smartphone, tablet computer, laptop computer, or any otherportable electronic device. The compressed sensor data may be compressedand/or stored on a user's wearable device, such as a user's smartwatch.The compressed sensor data may be compressed and/or stored at a remoteserver. The compressed sensor data may be compressed and/or stored usingany data compression and/or storage technique as is known to one havingskill in the art. The compressed sensor data may require less than 2,less than 5, less than 10, less than 20, less than 50, less than 100,less than 200, less than 500, or less than 1000 times as much storagespace as the uncompressed raw sensor data.

In some embodiments, step 1640 may further comprise the transmission ofthe analyzed data to a user's mobile device, such as a user'ssmartphone, tablet computer, laptop computer, or any other portableelectronic device. The transmission may be via a wired communicationchannel The transmission may be via a wireless communication channel.The wireless communication may be via Bluetooth communication. Thewireless communication may be via Wi-Fi communication. The wirelesscommunication may be via any other wireless communication known to onehaving skill in the art.

In step 1650, the results of the integration and analysis procedure areutilized to adjust one or more sensor parameters if necessary. Forinstance, one or more sensors of the sensing module may be selectivelyactivated or deactivated. One or more sensors of the sensing module mayhave its sensitivity adjusted. One or more sensors of the sensing modulemay have its dynamic range adjusted. One or more sensors of the sensingmodule may have its sampling rate adjusted. One or more sensors of thesensing module may be reconfigured to collect more or less data. Forexample, a person moving though a city with spatially variable pollutionmay be likely to benefit from more frequent measurement of pollution, atthe cost of the sensing system consuming more energy. By contrast, ifthe person is sitting in a park (as revealed by GPS position andvelocity data) and the wind-speed (as reported by local fixedmeasurement stations) is low, the PM2.5 pollution sensor may not need tobe polled as frequently or could even be turned off, saving energy.

Step 1650 may also comprise the programming and/or customization ofsensors to provide personalized sensor settings. For instance, one ormore sensors may be programmed to detect a particular pollutant with agreater or lesser sensitivity based on a user's physiological needs(such as health status, medical condition, or allergies), activities(such as participation in athletic endeavors or commuting to work),and/or local environment (such as geographic location, proximity toknown sources of pollution, time of day, season, etc.). As an example, auser who is allergic to a particular allergen may utilize a sensor thatis programmed to detect the allergen with very high sensitivity. Incontrast, a user who is not allergic to the allergen may utilize asensor that is programmed to detect the allergen with very lowsensitivity. The sensors can be preprogrammed prior to use, by a user orby another entity.

In step 1660, the results of the integration and analysis procedure aretransmitted to a central computer (e.g., a server). The central computermay store additional information that may be beneficial to determining auser's personalized pollution score, as described herein. For instance,the central computer may store pollution data from other sources such asfixed roof-top sensors and other humans wearing mobile sensors. Themeasurements from one or more sensors of the sensing module may beconveyed to the central computer, where the values are compared withother data sources such as pollution levels reported from fixedmonitoring stations or other people wearing pollution sensors. Thecentral computer may aggregate the data and utilize statisticaltechniques to identify individual sensor systems that are reportingunreliable and/or incorrect values. Gradual or sudden changes in thesignal output of any one sensor may therefore be remotely detected.Depending on the nature of the discrepancy and the fault, thisinformation may be used to take corrective actions. For example, whenthe central computer detects sensing defects, a replacement sensorsystem may be sent to a user. Alternatively, the central computer maysend a new set of calibration data, allowing it to be applied to thelocal sensors to maintain or improve sensing performance.

In step 1670, a personalized pollution score is produced. Thepersonalized pollution score may be produced by combining local andcloud data to produce data bearing on the health of a user. Forinstance, information from a pressure sensor and a geometrically definedaperture may be combined to determine the amount of air entering thehuman lung. By integrating this volumetric flow over time, it may bepossible to obtain an estimate of the total amount of air that has movedinto the lung in a given time period, such as minute, day, week, month,or year. By combining this information with pollution data obtained fromlocal or remote sensor data (such as a pollution sensor of the sensingmodule or local pollution data obtained from a cloud-based storagesystem), the cumulative pollution exposure of the individual may becalculated. The cumulative exposure may be calculated as the product ofthe total air volume and the measured or estimated local pollutionlevel.

The cumulative exposure E

(t) may be calculated at each time point t according to:

E?(t) = ∫₀^(t)V_(inhale)(t^(′)) * P(t^(′), l)dt^(′) ?indicates text missing or illegible when filed

Here, V_(inhale)(t

) is the instantaneous volume of air inhaled and P(

) is the instantaneous local pollution level at the location l.

The personalized pollution score may account for variations infiltration performance of the filter over time. For instance, thecumulative exposure may be calculated by factoring in the filterperformance:

E?(t) = ∫₀^(t)V_(inhale)(t^(′)) * P(t^(′), t) * η(t^(′))dt^(′) ?indicates text missing or illegible when filed

Here,

is the instantaneous filtration capture performance ranging from 0 to 1relative to some baseline.

The personalized pollution score may account for personal medicalinformation. For instance, the personalized pollution score may becalculated using only information about a person's exposure to aparticular pollutant, such as an allergen. As an example, a personalizedpollen exposure E

may be calculated according to:

E_(poll)(t) = ∫₀^(t)V_(inhale)(t^(′)) * P_(poll)(t^(′), l) * η_(poll)(t^(′))dt^(′) 

Here, P

is the instantaneous local pollen level at location l and

is the instantaneous pollen filter capture performance.

The personalized pollution score may combine two or more health-relevantparameters, such as both PM 2.5 levels and personal medical information,such as an allergic condition. For instance, for a person with allergieswho also wishes to minimize pollution, the PM 2.5 exposure and allergenexposure may be combined to calculate a weighted total exposureaccording to:

E_(total)(t) = ∫₀^(t)V_(inhale)(t^(′))(w_(PM2.5) − w_(poll))P_(PM2.5)(t^(′), l)η_(PM2.5)(t^(′))w_(poll)P_(poll)(t^(′), l)η_(poll)(t^(′))dt^(′)

Here,

is a weighting factor for PM 2.5,

is a weighting factor for pollen,

is the instantaneous PM 2.5 level at location l, and

is the instantaneous PM 2.5 filter capture performance.

The personalized exposure metrics may be combined with epidemiologicaland clinical data to provide estimates of the amount of life time gainedby using the filtration device. For example, if lifelong exposure topolluted air in a city reduces the mean life expectancy of 75 years (inthe absence of pollution) by 15 years, an estimate of the life secondsgained by avoiding a pollutant for a period of 100 hours per year givena filtration efficiency of 80% may be calculated as follows:

Health effect of pollution=reduction of life expectancy/life expectancywithout pollutant=15/75=0.2.

Duration of filter usage per year=100 hours.

Estimated reduction of life expectancy without filter=100*0.2=20 hours.

Estimated reduction of life expectancy with filter=100*0.2*(1−filtrationperformance)=4 hours.

Estimated life seconds gained this year by usingfilter=(20−4)*3600=57600 seconds.

In step 1680, an alert is issued to the user. The alert may be issued ifthe integration and analysis procedure determines that an action must betaken by the user. For instance, improper sensor readings may indicatethe air filtration and sensing system is improperly positioned within auser's nose. In such case, the user may be prompted to reseat/adjust theposition of an air-filtering device present in his/her nasal cavity. Thealert may comprise an audible, visible, or tactile alert. For instance,the alert may comprise a sound played on the user's smartphone or otherportable electronic device, a message or graphic displayed on screen ofthe user's smartphone or other portable electronic device, and/or avibration of the user's smartphone or portable electronic device. Thealert may comprise an indication of the number of life seconds, lifehours, life days, life months, or life years that a person has gained byusing the filter.

A person of ordinary skill in the art will recognize many variations,alterations and adaptations based on the disclosure provided herein. Forexample, the order of the steps of the method 1600 can be changed, someof the steps removed, some of the steps duplicated, and additional stepsadded as appropriate. Some of the steps may comprise sub-steps. Some ofthe steps may be automated and some of the steps may be manual. Theprocessor as described herein may comprise one or more instructions toperform at least a portion of one or more steps of the method 1600.

The sensing analysis module described herein may contain softwareinstruction, algorithms, or sets of instructions to provide predictiveanalytics relating to air pollution conditions. For instance, thesensing analysis module may be configured to predict whether one or morepollutant levels are likely to increase or decrease. The sensinganalysis module may be configured to predict a rate of increase ordecrease in the pollutant levels. The sensing analysis module may beconfigured to predict which types of pollutants are likely to be presentat a given time and in a given location based, for instance, on thecurrent or predicted future weather conditions, the season, or the timeof day.

The sensing analysis module may be configured to search for informationon databases (such as the NCBI PubMed database, Google Scholar, or anyother database) related to pollutants and their impact on human health.Using these database sources, the sensing analysis module may beconfigured to predict the impact of pollution to a user (for instance,by providing a “pollution score” or a “health score” to the user basedupon the pollution in their area and the functionality of their filter),warn the user of imminent harm that may result from continued ingestionof polluted air, and/or provide recommendations of corrective action bythe user. For instance, the sensing analysis module may suggest that theuser utilize a different travel route, relocate to a different area,reduce or cease physical activity, utilize additional filtrationprotection, or switch filters. In some cases, the sensing module maysuggest that the user administer a medication. For instance, the sensingmodule may suggest that the user utilize an inhaler or a nasal spray.

The sensing analysis module may arrive at health conclusions utilizingadaptive learning models. For instance, the sensing analysis module mayutilize machine learning models, including supervising learning models,semi-supervised learning models, and/or unsupervised learning models.The sensing analysis module may utilize statistical techniques such asprincipal components analysis or convolutional neural networks. Thesemodels may be employed to infer which pollutants are of particularconcern to a user. The models may be dynamically adjusted according tochanges in a user's condition, such as the worsening of an allergy.

In some embodiments, the sensing analysis module can generate one ormore graphical user interfaces (GUIs) for displaying a plurality ofpollution and health metrics. The GUIs may be rendered on a displayscreen on a user device. A GUI is a type of interface that allows usersto interact with electronic devices through graphical icons and visualindicators such as secondary notation, as opposed to text-basedinterfaces, typed command labels or text navigation. The actions in aGUI are usually performed through direct manipulation of the graphicalelements. In addition to computers, GUIs can be found in hand-helddevices such as MP3 players, portable media players, gaming devices andsmaller household, office and industry equipment. The GUIs may beprovided in a software, a software application, a web browser, etc. TheGUIs may be displayed on a user device (e.g., on graphical display 112of user device 120 in FIG. 1). The GUIs may be provided through a mobileapplication. Examples of such GUIs are illustrated in FIGS. 17 through20 and described as follows

FIG. 17 shows a graphical user interface for use with an air filtrationand sensing device that displays a user's pollution exposure while usingthe device and the user's expected exposure without the device. Theuser's current location 1702 may be displayed. Additionally, pollutionmetrics may be displayed on the GUI. These metrics may include changesin pollution levels 1706 (e.g., of certain pollutants) plotted as afunction of time relative to a safe level 1704. In some cases, themetrics may indicate fluctuations in levels of a plurality of differenttypes of pollutants. In some embodiments, the relative reduction (e.g.,percentage reduction) in the user's exposure to the pollutants (usingthe exemplary pollution filtration and sensing device described herein)may be displayed in the GUI. Other metrics, for example the user'sbreathing rate and heart rate may also be displayed in the GUI.

FIG. 18 shows a graphical user interface for use with an air filtrationand sensing device that displays pollution levels in different locationsnear a user. The GUI may include a map 1802. The map may include a 2Dmap, such as an overhead map. The map may include a 3D map. The 3D mapmay be alterable to view the 3D environment from various angles. Solidrenderings, wireframes, or other types of imaging may be shown, asdescribed previously herein. Locations having high pollution levels maybe indicated on the map, for example using various graphical objects(e.g., a circle) 1804. Any shape and/or size of the graphical objectsmay be contemplated. A radius of the circles may be representative ofthe area extent of the pollution. For example, a larger circle mayindicate that a larger region is affected by the pollution, whereas asmaller circle may indicate that a smaller region is affected by thepollution. Different colors and/or shading may be used to differentiatethe pollution levels within each region. The colors can be provided asdiscrete colors or along a gradient. As an example, red color may beused to indicate that an area is experiencing severe air pollution,whereas yellow color may be used to indicate that another area isexperiencing mild to moderate air pollution. Any color scheme or anyother visual differentiation scheme may be contemplated. In someembodiments, the GUI may include a text box that notifies the user aboutthe current level of pollution in the area where the user is located.The level of pollution in the area (where the user is located) may beprovided relative to other areas, for example as a relative percentagevalue.

FIG. 19 shows a graphical user interface for use with an air filtrationand sensing device that displays a user's pollution exposure score. TheGUI may display a numerical value 1902 that is indicative of thepredicted impact of the pollutants on the user's health. A pollutionrating 1904 (e.g., “fair”) may also be displayed along with thenumerical value. Other metrics may also be displayed, e.g., temperature1906 of the surrounding environment, filter health 1908 showing theremaining life and/or filtering performance of the device, and powerlevel 1910 of the device. Additionally, a user can also view thepollution ratings and corresponding numerical values of other differentusers within the user's social circle.

In some embodiments, the graphical user interface may display the airquality at a location near a user as a function of time. The GUI mayinclude a heading and a display of daily air quality levels in aparticular locality. Different colors and/or shading may be used todifferentiate the air quality at different points in time during theday. The colors can be provided as discrete colors or along a gradient.As an example, red color may be used to indicate that an area isexperiencing severe air pollution, whereas yellow color may be used toindicate that another area is experiencing mild to moderate airpollution. Any color scheme or any other visual differentiation schememay be contemplated. In some embodiments, the GUI may include displaydaily air quality levels in a particular locality for the past week, forinstance, on the most recent Thursday, most recent Saturday, etc. Thechange in air quality levels may be observed over any period of time(e.g., by hour, week, month, quarter, season, year, etc.) and/or region.In some embodiments, the GUI may permit the user to specify any temporalrange and/or geographical location of interest.

FIG. 20A shows a perspective view of a nosebud that can be used in anair filtration and sensing device. The nosebud may comprise an upper lip2002 and lower lips 2004 and 2006. The upper and lower lips may beconfigured to engage natural pockets located within the nasal passages,as described later herein. FIG. 20B shows a cross-sectional view of thenosebud retention mechanism of FIG. 20A.

FIGS. 21A-D illustrate exemplary dimensions of a nosebud that can beused in an air filtration and sensing device. For example, FIG. 21Ashows a top view of a nosebud. FIG. 21B shows a first cross-sectionalview of the nosebud. FIG. 21C shows a second cross-sectional view of thenosebud when it is retained in the septum of the nasal passageway. Theopening of the nosebud can be formed having different dimensions, forexample as shown in FIG. 21D.

FIG. 22A shows a magnetic resonance image (MRI) of pockets within thenose that may accept an air filtration and sensing device comprising anosebud. As seen in FIG. 22A, the nasal passages have natural pockets2200 that lie directly above the nostril. These pockets may serve asanchoring points for retaining the nosebud of the air filtration andsensing device.

FIG. 22B shows an air filtration and sensing device comprising a nosebudthat is anchored in the pockets of the nose. The nosebud may include aretention mechanism. The retention mechanism may comprise an upper lip2002 and lower lips 2004 and 2006. The upper and lower lips may beconfigured to engage the natural pockets 2200 to anchor the nosebud inplace on the user's nose, without requiring the use of one or moreexternal fixation devices.

FIG. 22C shows a first step of inserting a nosebud of an air filtrationand sensing device into the nose. The nosebud may be inserted into thenose at an angle in order to slide past the cartilaginous structures ofthe nostril. The nosebud may be made of a flexible material, such as anorganic polymer. The flexible material may allow the nosebud to becompressed into a smaller volume as it is inserted into the nostril, toaid in moving past the cartilaginous structures of the nostril.

FIG. 22D shows a second step of inserting the nosebud into the nose. Thesecond step may comprise rotating the nosebud in a front-to-back motionto move past the cartilaginous structures of the nostril.

FIG. 22E shows a third step of inserting the nosebud into the nose. Thethird step may comprise anchoring the nosebud in the natural pockets ofthe nasal passage. Once the nosebud is in place, the compression forceis released. This causes the flexible material to expand to its originalshape and/or size to fill at least a portion of the nasal passage,thereby anchoring the nosebud. Accordingly, the nosebud can be affixedto the user's nose, and can maintain a desired portion without requiringthe use of one or more external fixation devices.

In some cases, the nosebuds may have a size and shape that is customizedto fit a user's nasal passages. For instance, the nosebuds may have asize and shape that fills a majority of the user's nasal passage. Thenosebuds may fill more than 50%, more than 60%, more than 70%, more than80%, more than 90%, more than 95%, or more than 99% of a user's nasalpassage. The nosebuds may comprise a sealing edge. The sealing edge maybe configured to allow seating of the nosebud at the narrowest portionof the user's nasal passage during inhalation. The sealing edge mayprevent leakage of air past the nosebud during inhalation. In somecases, the sealing edge may allow partial leakage of air duringexhalation. In this manner, the resistance to airflow during exhalationmay be decreased.

While preferred embodiments of the present disclosure have been shownand described herein, it will be obvious to those skilled in the artthat such embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the disclosure. It should beunderstood that various alternatives to the embodiments of thedisclosure described herein may be employed in practicing thedisclosure. It is intended that the following claims define the scope ofthe disclosure and that methods and structures within the scope of theseclaims and their equivalents be covered thereby.

What is claimed is:
 1. A method of analyzing and displaying sensor datafor pollution and user health monitoring, the method comprising:receiving the sensor data collected by a plurality of sensors, whereinthe plurality of sensors comprise: (1) a first set of sensors located inproximity to a respiratory passageway of a user, and configured tocollect sensor data associated with one or more elements in air inhaledby the user, and (2) a second set of sensors located remotely from theuser and configured to collect a plurality of different sensor data; andanalyzing the collected sensor data to thereby generate a plurality ofpollution and health metrics including a health recommendation that arespecific to the user, wherein the plurality of pollution and healthmetrics are configured to be displayed as a set of graphical visualobjects on a graphical display of at least one user device.
 2. A methodof displaying sensor data for pollution and user health monitoring, themethod comprising: receiving an input from a user on a user device,wherein the input comprises a request from the user associated with aplurality of pollution and health metrics including a healthrecommendation that are specific to the user; and displaying, inresponse to the received input, the plurality of pollution and healthmetrics as a set of graphical visual objects on a graphical display,wherein at least one of the graphical visual objects is configured tochange in real-time to reflect changes in the plurality of pollution andhealth metrics as the metrics are being monitored by a plurality ofsensors.